September Insights On Big Data For Marketing, Sales & E-Commerce

#1 – TARGETING THE OMNI-CHANNEL CUSTOMER

“The use of Big Data has become a critical force in growing revenues. Big Data Analytics is helping retailers stay in front of a new breed of consumer, the omni-channel shopper.” – Durjoy Patranabish: Former Senior Vice President of Analytics at Blueocean Market Intelligence.

Over the last decade, the field of marketing has undergone rapid changes, moving from mass-marketing to a more personalised, individual communication approach. Analytics tools allow us to segment customers based on preferences, and track the progress of our marketing campaigns.

“Consumers can now engage with a company in a physical store, on an online website or mobile app, through a catalog, or through social media. They can access products and services by calling a company on the phone, by using an app on their mobile smartphone, or with a tablet, a laptop, or a desktop computer.” – Mike Stocker: Vice President of Business Development at Vidyard.

With multiple channels available to purchase from, marketers are faced with the challenge of providing consistency in the customer experience at every potential touchpoint of their purchasing journey. From monitoring web traffic on Google Analytics to launch promotions at optimal times, to investing in SEO services to boost keyword rankings, to building customer journey maps, marketers need to be in the know-how about what motivates their customers in order to deliver what they’re looking for.

 

#2 – WHAT GETS MEASURED, GETS MANAGED

“The most successful companies are digging deep into the data driven research available to them, giving them a leg up on customer retention and bolstering the bottom line.” – Jennifer Havice: Website Copywriter & Online Marketing Strategist at Make Mention Media & Communications.

Big or small, every business can reap the benefits of data analytics tools that give you the insights you need to increase your marketing ROI. We’ve rounded up some of the most popular tools in the industry.

 

Mixpanel

A platform for following the digital footprint of each of your users across both mobile and web devices. This tool allows for for flexibility and customisation, no matter what your role within the business, so you can get the precise knowledge you’re after about your product or service.

 

Kissmetrics

A popular customer intelligence web analytics platform to help track the customer journey, aimed at businesses looking to optimise their digital marketing and boost conversion rates.

 

Google Analytics

A seamless, all-inclusive picture of your business performance. Google Analytics shows you how your campaigns are doing, which customer channels have the highest conversion rate, and allows to set goals and targets, so you you can track your progress over time.

 

Kapost

Helping businesses “turn content into customers,” this platform is used to drive content operation and realise your b2b marketing strategy. It can be integrated with tools like WordPress, Hootsuite and Marketo.

 

#3 – IDENTIFYING OPPORTUNITIES

“The biggest challenge for most eCommerce businesses is to collect, store and organise data from multiple data sources. There’s certainly a lot of data waiting to be analysed and it is a daunting task for some E-commerce businesses to make sense of it all.” – Jerry Jao: CEO & Founder of Retention Science.

Not only does data analytics increase revenue potential with your current customers, it can also be used to identify and attract new markets to tap into.

“Large online vendors can scale their offerings with Big Data and meet specific customer needs. But Big Data also allows to predict customer needs and enable a future optimisation of the product portfolio. So with Big Data, it is possible to optimise the stock costs.” – Big Data Made Simple.

Online retailers can now make better informed decisions while also forecasting for the future. Wouldn’t you love to know what you’re customers would like to buy in advance, and how much they’d be willing to spend? with predictive analytics, you can.

Predictive analytics involves extracting information from your existing data to determine patterns and predict future outcomes and trends. Platforms like RapidMiner and Lattice help identify potential anomalies, service opportunities, reduce the uncertainty of outcomes and score better sales leads.

 

 

 

For more resources, please see below:

 

The Omni-Channel Customer

What Is Omnichannel?

Targeting Omni-Channel Shoppers

The Definition of Omni-Channel Marketing – Plus 7 Tips

Ten Ways Big Data Is Revolutionising Marketing & Sales

 

Marketing Tools

Kapost

Mixpanel

Kissmetrics

8 Big Data Solutions For Small Businesses

Big Data Trends: Top Eight Analytics Lessons For Business

4 Marketing Analytics Tools That Are Shaping The Industry

 

Identifying Opportunities

Lattice Engines

RapidMiner: Data Science Platform

Why Big Data Is A Must In E-Commerce

How Predictive Analytics Is Transforming eCommerce & Conversion Rate Optimisation

 

 

 

Career Opportunity For Linux Administrators At Contexti | Big Data Analytics

Location: Sydney, Australia

 

ABOUT US

Contexti is a specialist Big Data Analytics Solutions company serving the Australian market. With strong partnerships with AWS, Cloudera, Talend and Mesosphere, we provide training, consulting and managed services for some Australia’s leading enterprises where data is at the heart of their business transformation.

We are a small but growing Sydney based team; most work is performed from our CBD office location, but occasionally we will work from customer sites. We prioritise cultivation of positive relationships with customers and seek to provide a good team atmosphere with a healthy work-life balance. While not for everyone, a significant portion of us are also on a quest to identify and consume the best Ramen and Laksa Sydney has to offer.

 

THE OPPORTUNITY

We’re looking for an experienced Linux Administrator who will be responsible for maintaining, designing, implementing, and monitoring predominantly cloud based systems. Collaboration with other team members is essential as we continue to develop automation strategies and deployment processes. You will become an integral part of the team, taking ownership of implementation work as well as working ad hoc problems through to resolution.

Your responsibilities:

  • Implement, maintain and support solutions that enable positive outcomes for our customers.
  • Take on complex integration problems making diverse application components work together.
  • Help tune performance and ensure high availability of infrastructure.
  • Design and develop infrastructure monitoring and reporting tools.
  • Develop and maintain configuration management solutions.
  • Develop test automation frameworks in collaboration with rest of the team.
  • Create tools to help teams make the most out of the available infrastructure.

 

ABOUT YOU

The person:

  • Looking for purpose in your work and the company you work for
  • You’re ready to learn, grow and contribute
  • You love to help customers and team members

 

You have the following skills:

  • Experience with Linux servers in virtualized environments.
  • Familiarity with the fundamentals of Linux scripting languages including Bash and Python.
  • Experience installing, configuring, and maintaining services such as Apache Httpd, MySQL, nginx, etc.
  • Exposure to Kerberos, and better still experience integrating Linux with Active Directory, e.g. SSSD, Centrify, etc.
  • Basic knowledge of configuration management tools (e.g as Ansible, Puppet and Chef).
  • Exposure to infrastructure versioning, provisioning and continuous integration tools (e.g Jenkins, HashiCorp TerraForm/Vagrant/Packer).
  • Familiarity with load balancing (e.g. HAProxy), firewalls, etc.
  • Experience with containerisation technologies, such as Docker, Apache Mesos, DC/OS, etc.
  • Experience with prominent core AWS services (VPN, VPC, EC2, EBS, S3, IAM, CloudWatch etc).
  • Hadoop experience would be an added bonus, but is not a requirement – you can learn this from us.
  • Most likely you will have a Computer Science Degree, you will certainly have relevant industry experience.

 

HOW TO APPLY

  • You must hold the right to work in Australia to be considered for this role.
  • Please send your resume and short cover note to jobs@contexti.com

Note to Recruiters – We will be filling these roles directly.

For more resources, please see below:

How To Succeed On Your Big Data Journey
5 Tips On How To Land A Big Data Job In Australia
Data & Analytics Australian Recruitment Market Insights By FutureYou

 

Five Big Data Skills That Will Help You Get Ahead In The Tech Industry

“The IT labor market is still very hot. The candidate is very much in the driver’s seat,” Jason Hayman: Market Research Manager at TEKsystems.

Businesses need confidence in their decision making process. Today, this means turning to the factual and reliable information derived from data. With many organisations looking to stay ahead of the competitive curve with techniques like data science and deep learning, this leaves a big window of opportunity for those with these in-demand skills.

If you’re a job seeker looking to up your analytics game, you may want to consider developing these skills:


#1 – HARNESS THE POWER OF BI TOOLS

“Today, tools such as Tableau and Power BI are a must to obtain business information in the correct desired form. This includes setting up the data source, data cleaning mechanism and analysis algorithms.” – Rhucha Kulkarni: Associate Features Editor at ReadITQuik.

Business Intelligence (BI) tools are applications, programs and software used to locate, analyse and document data. It is used to simplify the flow of data, making it more manageable. Access to accurate information in the right place and right form is a must-have for businesses looking to make the most of data in a reliable and time-effective way.

 

#2 – CONVERT KNOWLEDGE INTO ACTION

“Companies are trying to make sense of what the data can tell them about how to do business better. That, in turn, is fueling demand for people who can make sense of the information.” – Yuki Noguchi: Correspondent at NPR.

The ability to understand and utilise data to drive success can make you a big asset to an organisation. It’s not just about monitoring data, it’s about developing a solution strategy with the insights you’ve generated. Learning how to best utilise BI software can help you achieve this.

“This technology provides companies with actionable insights and greater visibility into their customers’ buying habits and trends so that they can always stay one step ahead of the competition.” – Paul Black: Data Marketing Magazine.

 

#3 – STAY AHEAD OF THE COMPETITION WITH PREDICTIVE ANALYSIS

“Today’s business applications are raking in mountains of new customer, market, social listening, and real-time app, cloud, or product performance data. Predictive analytics is one way to leverage all of that information, gain tangible new insights, and stay ahead of the competition.” – Rob Marvin: Assistant Editor at PC Mag.

The ability to use existing data to identify future risks and opportunities is an essential skill in the field of Data Analytics. Many industries like marketing, finance and healthcare can benefit from the forecasts created by statistical modeling, machine learning and other technologies.

“These techniques can provide managers and executives with decision-making tools to influence upselling, sales and revenue forecasting, manufacturing optimization, and even new product development.” – Georgetown University.

 

#4 – ENHANCE YOUR PROBLEM-SOLVING SKILLS

“Businesses face complex problems every day, and they are forced to solve them quickly and efficiently. That’s where decision science comes in. This market needs proven methodologies and frameworks to follow in order to materially affect business outcomes.” – Tom Pohlmann: Chief Marketing Officer at AHEAD.

A large part of of identifying challenges, risks and opportunities when analysing Big Data comes from implementing the right tools and frameworks to generate these insights. However, human intuition is still an important quality.

“We know executives pay attention to what data and analytic tells them, that’s the science part of the equation. But we also know they rely heavily on the art of intuition.” – Dan DiFilippo – Consulting Clients and Markets Leader For China and Hong Kong at PwC.

Intuition is the ability to understand something instinctively, without the need for conscious reasoning. In the era of of big data however, being unable to explain your logic when you come to a decision is a risk. In a survey conducted by PwC, 59% of decision makers said the analysis they require relies primarily on human judgment rather than machine algorithms.

“Seizing the opportunity will require leaders who can weigh the power and influence of both artificial and human intelligence, finding a balanced path that makes the most of each unique capability.” – Hugo Moreno: Contributor at Forbes.

 

#5 – BE VERSATILE

“In an age of Big Data, having tech skills is important, but the pendulum might be starting to swing the other way. More companies are requiring a mix of technology and people skills.” – Stephanie Vozza: Writer at Fast Company

The ability to take on multiple roles can make you more valuable to a team, not to mention give you a competitive advantage.

“Competition for analytical talent is extreme. And preserving and maintaining a base of talent within an organisation is difficult, particularly if you view this as a core competency.” – Ruben Sigala: Chief Analytics Officer at Caesars Entertainment.

In the field of data analytics, the combination of both hard skills (technical) and soft skills
(communication) is crucial to your success.

“Many who are working in the field today have more than one role in their job. They may act as researchers, who mine company data for information. They may also be involved with business management. Around 40% work in this capacity. Others work in creative and development roles.” – Ronald van Loon: Director of Advertisement.

“The right talent will go find the right technologies; the right talent will go solve the problems out there.” – Victor Nilson: Senior Vice President of Big Data at AT&T.

 

For more resources, please see below:

 

Data Analytics

Intuition Is The Antidote To Big Data

Pros and Cons Of Predictive Analysis

How Companies Are Using Data Analytics

Making Advanced Analytics Work For You

How Companies Are Using Big Data And Analytics

The Search For Data Analysts To Make Sense Of Big Data

Predictive Analytics, Big Data and How To Make Them Work For You

How Most Successful Companies Effectively Leverage Data & Analytics For Problem Solving

 

Data Tools

7 Top Tools For Taming Big Data

All The Best Big Data Tools and How To Use Them

Use Big Data To Get (And Stay) Ahead Of The Competition

Top 10 Tools For Working With Big Data For Successful Analytics Developers

 

Data Trends

10 Big Data Trends To Get Ahead of Now

Data Analytics Trends You Must Incorporate

 

Data Skills

The Hard And Soft Skills Of A Data Scientist

How To Boost Your Career In Big Data Analytics

July Insights On Big Data & Business Transformation

It’s been a busy month in Big Data, and we’ve been deep in learning about what factors are driving the industry. We’ve translated our experience, research and insight into five key lessons.

Here’s what we’ve learnt this month.

 

#1 – PLAN & TEST FIRST, INTEGRATE LATER

“Big data has proven to be a valuable business asset, but using it to gain competitive advantage requires the right combination of strategy, technology and execution.” – Mahmood Majeed: Managing Partner at ZS Associates.

In all the excitement of implementing a Big Data strategy, It’s easy to get caught up in the hype of new technologies promising to do magical things with your data, and make hasty decisions that once integrated, can be disappointing.

To avoid this, team leaders of Big Data projects must ensure that expectations and output are aligned.

“Start by developing a strategy across the entire enterprise that includes a clear understanding of what you hope to accomplish and how success will be measured.” – Harvard Business Review.

 

#2 – SECURITY IS NOT AN AFTERTHOUGHT, IT’S A NECESSITY

“Big Data and analytics is showing promise with improving cyber security. 90% of respondents from MeriTalk’s new U.S. government survey said they’ve seen a decline in security breaches.” – SentinelOne.

With the volume of worldwide data reaching unprecedented levels, new cyber security threats are emerging daily. To combat this, an article in CSO discusses the benefits of using historical data to identify potential cyber attacks while also predicting future events.

“Using this historical data, you can create statistical baselines to identify what is ‘normal’. You will then be able to determine when the data deviates from the norm.This historical data can also create new possibilities for predictive models, statistical models, and machine learning.”

 

#3 – IT’S ABOUT QUALITY, NOT VOLUME

“Because Big Data presents new features, its data quality also faces many challenges.” – Li Cai & Yangyong Zhu: Fudan University.

As data evolves, new challenges emerge which is why it’s important for businesses to develop data quality standards. With the rise of insight-driven business models, the quality of the data used is key to making the right decisions. Leaders of Big Data projects must ensure that the data is accurate for the intended use.

“Data quality depends not only on its own features, but also on the business environment using the data, including business processes and business users.” – Data Science Journal.

 

#4 – BIG DATA + AGILE = SUCCESS

“The longer you take to find the data, the less valuable it becomes.” – Wired.

With recent advancements in technology, more emphasis is being placed on data agility and the importance of data-driven insights in real-time. “How fast can you extract value from your mountains of data and how quickly can you translate that information into action?” – tdwi.org.

Ian Abramson, former Director at EPAM Systems, describes the alignment of Big Data and Agile as “the infrastructure and framework to be successful.” He then goes on to talk about how this alignment enables focus and a clear picture of how to get from A to B. “ What is the question, what is the success factor, how will we get there, and who will be involved?”

At the 2016 International Conference on Ambient Systems, Networks and Technologies (ANT), experts in the field of Big Data were asked, “ What do you think is most important in the management of Big Data projects?” Interestingly, respondents rated three out of the Four Values of The Agile Manifesto as the highest in their answers, which were: cooperation with customers, people & communication, and working with software over comprehensive documentation.

 

#5 – SKILL-UP OR MISS OUT

“Is the world going to become a place in which automation is everywhere yet employment is scarce?” – Michael Grothaus: The Hanbury Literary Agency.

According to KPMG’s 2016 CIO Survey, data analytics is the most in-demand technology skill for the second year running, but nearly 40% of IT leaders say they suffer from shortfalls in skills in this critical area. “Big Data training is beneficial in meeting the demands of Data Management, faster decision making, better understanding of customers and tapping into the right demographic.” – Vikrant Singh: Senior Manager at Xebia Group International.

In a recent article , Sophia Bernazzani, Marketing Manager at HubSpot says, “The fact remains that some jobs will be replaced by machines – it’s the essence of any industrial or technological revolution. The good news is; some jobs won’t be strictly replaced – they just might be adjusted to account for new technologies.”

So how do we skill-up and adopt these new technologies into our businesses? “By training those already with the company, businesses get to keep valuable team members that already have experience with the enterprise while giving them some much-needed skills.” – Rick Delgado: Enterprise Tech Commentator & Writer.

“Training employees can never be a liability. It is in fact an asset, an investment to the company.” – Big Data Trunk.

 

For more resources, please see below:

 

Data Integration

How To Integrate Data And Analytics Into Every Part of Your Organisation

Charting An Effective Big Data Strategy

Big Data: The Management Revolution

 

Data Quality

Beyond Volume, Variety & Velocity Is The Issue of Big Data Veracity

The Challenges of Data Quality Assessment In The Big Data Era

Big & Fast Data: The Rise of Insight-Driven Businesses

 

Cyber Security

How Big Data Is Improving Cyber Security

Big Data Security Analytics: A Weapon Against Cyber Security Attacks

 

Data Skills

The Importance of Employee Training

Businesses And The Big Data Skills Shortage

Big Data Jobs Are Out There: Are you Ready?

The Importance of Big Data Training to Your Data Analysis Growth

10 Jobs Artificial Intelligence Will Replace (and 10 That Are Safe)

 

Data Agility

Big Data and Agile: The Perfect Marriage

Agile Project Management And Its Use in Big Data Management

Looking For A Career In Big Data Engineering? We’re Hiring At Contexti

Location: Sydney, Australia

Big Data is changing the world, and adapting to an era of more data-driven decision making requires developing talent, processes and organisational muscle. With the rapid pace of innovation and growing demand for Big Data, the data engineering space has more opportunities than ever before.

Contexti is a specialist Big Data Analytics solutions company serving the Australian market. With expertise in Commercial Data Strategies, Big Data Platforms, Data Science & Insights, we enable our customers to drive growth, innovate and compete.

As a trusted Big Data specialist solutions partner for Amazon Web Services (AWS), Cloudera, Mesosphere and Talend, we provide Advisory, Consulting, Training and Managed Services for tier one clients.

Check out the work we did with Seven West Media on audience engagement for the Rio Olympic Games:

Seven West Media Taps Cloudera and Contexti For Big Data Solution For Rio Olympics

Due to strong organic growth, we are now looking for additional team members.

 

The Opportunity

We’ve got a number of entry level and mid-level opportunities for engineers keen on developing their careers in Big Data Analytics.

Our consultants get to develop their technical and client service skills working with leading Cloud and Big Data technologies.

We provide both internal and external training, and you will get to work alongside some of the best in the industry.

 

About You

The person:

  • Looking for purpose in your work and the company you work for
  • You’re ready to learn, grow and contribute
  • You love to help customers and team members

You have one or more of the following:

  • Experience in Data Engineering (SQL)
  • Experience with Hadoop, Spark, EMR, Oozie
  • Experience with infrastructure and automation
  • Experience with Amazon Web Services (AWS)
  • Experience working with DevOps tools, Chef, Ansible, Puppet

 

How to Apply

  • You must hold the right to work in Australia to be considered for this role.
  • Please send your resume and short cover note to jobs@contexti.com

Note to Recruiters – We will be filling these roles directly.

 

 

 

Data & Analytics Australian Recruitment Market Insights by FutureYou

With the launch of their data and analytics practice lead by Caroline McColl, FutureYou Executive Recruitment have produced an insightful report on the data and analytics recruitment market in Australia. This 3 page reports gives a great snapshot on:

  • Market Moves – who are the new Chief Data Officers, Heads of Analytics and Heads of Insights?
  • In Demand Skills – do you have what the market is looking for?
  • Industry Pain Points – key challenges in getting value from data – are you having the right conversations?
  • Candidate Spotlight – what’s the going salary rate, for which skills and industry experience?
  • Skills Testing – why would you get your candidates skills tested?
  • Top 5 Drivers for Career Advancement – What’s the ideal combination of skills across business, technology and data science that will advance your career in big data analytics?

FutureYou have kindly permitted Contexti to share this report with those interested. If you’re hiring or are seeking to get hired this report will provide some food for thought.

5 Tips On How To Land A Big Data Job In Australia

In today’s Australian job market if you’ve got some Big Data experience, you’re mostly likely getting approached by recruiters and are probably spoilt for choice. If that’s the case, you don’t need to read on. This article is for the rest of you, who have heard about this ‘Big Data’ thing and are wondering how to get your foot in the door.

Given Contexti’s focus on the Big Data Analytics market in Australia, we’re fortunate to be aware of and in many cases involved in a broad range of Big Data Analytics related conversations, deals, projects, partnerships, hires, fires and events across Australia. The single biggest challenge we constantly hear about is the shortage of qualified and experienced ‘Big Data’ people.

While we don’t advise our customers to drop their standards in the quality of their hires, we do strongly warn against holding on to the belief that there is a magical unicorn big data guru out there. Instead we suggest organisations hire professionals with the right fundamentals (e.g. fit for culture & values, coachable, possess skills in certain technologies or analytics methods, etc) and implement a plan to develop them into capable Big Data Analytics practitioners.

Similarly we’ve found ourselves having conversations with a broad range of professionals, some who are just starting our their careers and are thinking about graduate roles while others with decades of experience who now want to transition into a career in the growing Big Data Analytics space.

Like everything else in business and life there are no silver bullets, but if you approach this in a strategic and tactical manner, you will massively improve the odds in your favour.

So here are five tips to help you land a big data job in Australia:

#1 Define your target role

While ‘data scientist’ sounds like an exciting role, it may not be the right entry point for you. You want to get into a role where you will learn and where you will also quickly add value by bringing something to the table. To do this, think about your ‘home ground advantage’, what skills, experience or connections do you already have and map it to the closest Big Data role in the an industry most suitable to you.

Some real-world examples we are aware of:

  • Our own Damion Reeves at Contexti transitioned from being an experienced Database Administrator (DBA) with years of experience in infrastructure, Oracle and SQL to a Big Data Platform Engineer. While Hadoop and Spark were technologies he needed to learn, his underlying experience with Linux and UNIX, capabilities in shell scripting and knowledge of enterprise support and service protocols were immediate value-adds to Contexti and to our customers.
  • Our client Sharmaine Salis Head of Data Architecture at Seven West Media transitioned from a traditional Business Intelligence / Data Warehouse solutions role into a Big Data / Cloud Architect role, leading one of the most successful big data projects in Australia which underpinned Seven’s Rio Olympics games coverage.
  • One of our Hadoop & Spark training students, MingJian Tang currently a Cyber Security Data Scientist at the Commonwealth Bank of Australia (CBA), transitioned into this role from a statistics and data mining background.
  • Broader in the field we’ve seen someone with solid Telco background move into a Big Data Strategy role for one of the Telcos trying to monetise their data assets.

So the take-aways are:

  • There are many potential Big Data Analytics roles (Commercial Strategist, Platform Architect, Data Architect, Platform Engineer, Data Engineer, Analyst, Data Scientist, Project Manager, Quality Assurance, Sales, Business Development, Customer Success etc).
  • No one-person will be qualified to do all the available roles in Big Data.
  • Find your home ground advantage and target a role that gets you excited and one where you can add value quickly.

#2 Skill up

You will massively improve your chances in landing a role if you’ve invested in skilling yourself up. The one obvious benefit is the theoretical and in many cases the practical knowledge you will gain by attending formal training. The other not so obvious benefit is the network of relationships you will create with the instructor and other class participants. Depending on the role, your budget, time availability etc there are many courses to take advantage of. Here are some of the short to long training and certification programs we are aware of:

#3 Network

An important factor in landing a new role is ‘who you know and who knows you’. Networking enables you to to build relationships, get known, learn something new and contribute. There are many meetup groups and networking events. Here are some of the ones we attend:

#4 Be found

There are many ways to get your name out there and to be found. Speaking at events and meet ups, writing guest blogs posts, publishing your work in online forums (GitHub, Slideshare etc), getting active on Twitter and Quora. The simplest and most obvious one however is to put effort in your LinkedIn profile. After you consider your target role and your home ground advantages (existing skills, industry experience etc) as well as your training and up-skilling strategy, you should update your LinkedIn profile.

Your profile should be authentic. This means stating correctly what you have done, skills you possess and how much experience you actually have. Further an authentic profile should include objectives, aspirations and current activities you are undertaking to improve yourself giving the potential recruiter an idea of not only where you’ve been but a view of where you are headed.

A recent example was when I was doing a search on LinkedIn for anyone who had included “Data Science” in their profile. I came across a professional who had recently completed a data science course in addition to having a math and statistics major and hands-on actuarial work experience. His LinkedIn headline said ‘Aspiring Data Scientist’. The word ‘aspiring’ gave me an indication of where he was headed and what he was looking for yet it was authentic as he wasn’t claiming to be an experienced data scientist.

This approach can be applied to your LinkedIn headline and your summary where you can include your ‘elevator pitch’ of who you are, where you’ve been, what your great at and where you are heading.

#5 Look for early signals

To narrow down your targeting efforts and improve your odds, look for early signals that might lead you to a future job opportunity. Typically this will be keeping your eyes open on LinkedIn, subscribing to relevant industry news and blogs, reading mainstream business and technology news and being an active networker. Early signals you should keep your eyes on include: companies announcing changes in strategy, appointment of new leaders, new partnerships or vendors winning contracts.

For example in the last six months in Australia there have been a number of executive movements in the Chief Data Officer and Chief Digital Officer roles, this kind of appointment usually indicates a company is reprioritising ‘data’ as a strategic priority and is usually followed by a restructure and a recruitment drive. There have also been a number of public announcement of data deals and data partnerships as well vendors announcing contracts with new customers or publishing case studies of success stories with existing customers.

All of these are early signals that will give you hints on people, companies, technologies and deals to follow and target in order to land your next big data job.

 

By: Sidney Minassian – Founder & CEO, Contexti – Big Data Analytics

 

Subscribe for updates on the latest big data analytics training courses, industry events and career insights.

7 Ways to Increase Your Value as a Data Scientist

As a Data Scientist, you are currently in high demand and in a hot market. That is not about to change any time soon.

So on the one hand, you can ignore this article.

Yet on the other hand, given the 40+ big data projects we’ve delivered for Contexti clients, we’ve had a lot of interactions with Data Scientists inside companies of varying sizes and industries and my observation is that Data Scientists are leaving value on the table for themselves and are therefore limiting their career and leadership trajectories.

There are probably a number of reasons for this, but primarily it’s because Data Scientists are allowing themselves to be pigeonholed into being ‘just the data person’.

You will have greater value as a Data Scientist when:

  • you have established credibility BEYOND being just the data person
  • you get a seat at the strategic table to discuss the business and customer context; and
  • your efforts result in measurable impact on the organisation

So here are 7 ways you can increase your value as Data Scientist:

#1 Know the business

When you are on the ‘same page’ as the business you will engender a deeper level of conversation, you will ask better questions, you will push back on the right issues and overall you will command the respect of your colleagues beyond your analytics brilliance. You should know and be able to quickly articulate key business and profit details such as:

  • what industry you are in;
  • what are the top performing product / service lines;
  • what are your best channels to market;
  • who are your primary customers;
  • who are your most strategic partners (and why? what’s in it for them);
  • who are your biggest competitors and what is their strategic or competitive advantage;
  • who are your likely unexpected competitors and
  • who is going to disrupt you or your industry externally ◦ etc

 •

#2 Get to know your Customer’s Customer

Don’t settle with just understanding the ‘Marketing’, ‘Risk’, ‘Operations’ departments as your customers. While they may be your direct customers, you should also care to learn about your customer’s customer. Who are they serving? Request that you join your customer when they meet with their customers, this will give you another level of context, perspective and depth in understanding the ‘end customer’. By getting to know your customer’s customer, you will think differently about the problem you are solving and you will have a different conversation and create a higher level of rapport with your direct customer.

#3 Beyond the WHAT and the HOW…. Ask WHY

It’s easy to jump into problem solving mode. The question is are you solving the right problems? Often you’ll have clarity on ‘What’ you need to do and given your skills you’ll know the ‘How’. To increase your relevance and value, make sure you are also clear on the ‘WHY’. By understanding the ‘Why’ you will think creatively about the problem and solution – if you understand the ‘why’ you may recognise you’ve been tasked with the incorrect ‘what’. Even the conversation of the ‘why’ will help build trust between you and the people you are collaborating with. •

#4 Step away from the data

To get context and perspective, step away from the data, models and charts and put yourself in position to observe what you are meant to be measuring or solving in its physical form. Things beyond the numbers will jump out at you that can dictate the success or failure of your solutions. Certain industry nuances, the political landscape of the organisation, the organisation’s readiness to adopt change, culture and values, the user experience and the customer journey will all give you greater levels of insight beyond the numbers.

#5 Seek the ACTION

The best insights, not executed will create zero value. So in addition to understanding the ‘why’, seek to understand the ‘actions’ that will be taken given your insights. Often this will be outside of your domain or direct sphere of influence and that is exactly the point. To move beyond being ‘just the data person’ you should seek clarity (accountability) from your colleagues on what will be done with your insights, in what time frame and how you and your colleagues will be informed about the impact.

#6 Build bridges with people

The right team composition is critical to ensure success with data projects. In addition to Data Scientists you need customer advocates, subject matter experts, platform architects, platform engineers, data engineers, platform administrators, marketing/operations/risk/legal experts etc. So as a Data Scientist, build relationships with these colleagues, they are all important contributors to delivering success. You will learn from them, you will teach them and most importantly you will have established a bridge, which will raise your value. •

#7 Over-Communicate

We often hear Data Scientists need to be ‘story tellers’, often this is only interpreted as ‘story telling with the numbers’. I suggest that you should not to wait for just the ‘story with the numbers’ part of the project before you find your voice. It’s important to bring people on the journey and you can do this by communicating (over communicating). Share with them your understanding of the ‘business’, your knowledge of the ‘customer’s customer’, the ‘why’ of what you are working on, the insights you gained by ‘stepping away from the numbers’ and how you expect the your insights to be turned into ‘actions’ to deliver value. Share with people your experimentations, your success, failures and learnings. You will learn from their feedback and corrections, you will build respect with your openness and willingness to share and teach and you will establish your voice in your organisation.