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Senior Applied Data Scientist
  • Python
  • Spark
  • SQL
  • Machine Learning
  • Data Mining
  • Modeling
  • Hadoop
dunnhumby
London
126 days ago
dunnhumby is the world’s leading customer science company. We analyse data and apply insights from nearly one billion shoppers across the globe to create personalised customer experiences in digital, mobile, and retail environments. Our strategic process, proprietary insights, and multichannel media capabilities build loyalty with customers to drive competitive advantage and sustained growth for clients. dunnhumby employs over 2,000 experts in offices throughout Europe, Asia, Africa, and the Americas and works with a prestigious group of companies including Tesco, Monoprix, Raley’s, Macy’s, Coca-Cola, Procter & Gamble, and PepsiCo. For more information, please visit us at www.dunnhumby.com.
dunnhumby is looking for a talented Senior Applied Data Scientist!

You will lead and execute projects to distil complex problems into compelling insights, using the best of dunnhumby science and make recommendations that resonate with clients and lead them to action.
What you'll be doing:
  • Build strong relationships with internal contacts & external clients to ensure full understanding of client challenges, growth strategy and agreed measures of success for the project.
  • Investigate and implement the most appropriate analytical technique for each project, role modeling the re-use & further development of global solutions or code written by others.
  • Deploy, and mentor the team to deploy, data science algorithms and market products on chosen tech stack for efficient and cost-effective delivery.
  • Lead and execute projects that distil complex problems into compelling insights that resonate with clients and lead them to action.
  • Spot opportunities to grow client engagement by proactively solving client’s strategic questions, using a mix of products and advanced data science techniques that support executive decision making and call to action.
  • Participate in client meetings as required to present methodology and solutions through effective story telling techniques.
  • Work closely with global products team to provide market feedback for enhancing an existing product offering or augmenting the catalogue with a market-based product that can become global offering.
  • Ensure smooth running of your projects and support junior team members with their projects.
  • Lead by example by following dunnhumby Quality Assurance processes, ways of working and coding standards.
  • Provide advice and support to colleagues to resolve challenges and support code reviews.

Who you’ll get to work with:
Within dunnhumby you’ll work with
  • Applied and Research Data Scientist teams
  • Client / Commercial teams
  • Global Capability teams
  • Data Science Engineering teams

Externally, you’ll frequently be in contact with:
  • Senior Retail/Customer Packaged Goods Analysts and Insights contacts
Qualifications
What you'll need:
  • Bachelor’s degree or equivalent in Mathematics, Economics, Applied Statistics, Computer Science, Physics, Engineering or related field.
  • Experience focussing on the practical & pragmatic use of data and a passion for connecting your work directly to the customer experience, making a real and tangible impact.
  • Experience with handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL / Python.
  • Analytical Techniques
  • Analytical Technology
  • Desk Research
  • Prototyping
  • Quality Assurance and Testing
  • Statistical Modelling
  • Programming (Python, SQL, R, …)
  • Data Interpretation/ Insight Analysis
  • Data Visualisation
  • Insight Storytelling
  • Client relationship building and management
  • Presentation skills

A plus if you also have:
  • Master’s degree or equivalent in in Computer Science, Artificial Intelligence, Machine Learning, Applied Statistics, Physics, Engineering or related field.
  • Programming experience on any standard data mining and modelling packages such as Python and R.
  • Experience of applying advanced statistical models and machine learning algorithms to solve a variety of

Life at dunnhumby
dunnhumbians are passionate people who always start with the customer, we are ambitious and decisive, we listen and understand, innovate and explore, and work together to grow one dunnhumby.
  • Here you'll be part of a culture that welcomes participation and discussion at all levels.
  • You’ll get to work in an internationally collaborative environment alongside teams of ambitious, inquisitive and forward-thinking individuals.
  • We believe that learning and development never stops and provide opportunities to feed your curiosity to understand, improve, and learn; encouraging everyone to build on the best of what we do.
  • You'll have the opportunity to work with ground-breaking technology delivering extraordinary impact for our customers.
  • We’re a great believer in work-life balance offering flexible working hours plus an extra day off on your birthday.
  • dunnhumby's spirit of community and the diversity of our people's skills, backgrounds and experiences makes us stronger. We continuously seek to build an environment of inclusion, equality and respect because we know that will make us the best business we can be.
Our approach to Flexible Working
  • At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work. We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process.
Discover where a career with us can take you. Meet our people on YouTube to learn about the diversity in career paths across dunnhumby. For more about our culture and to explore the benefits we offer visit our Careers site.
Primary Location: United Kingdom-LondonJob: Data and Analysis-Applied Data ScienceJob Type: RegularJob Posting: Jun 18, 2020, 4:21:08 AM

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