Senior Data Science /Full Stack Engineer

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Gurgaon, Gurugram, Haryana
In-Office
eCommerce • Retail
The Role

dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. 

dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro.

 

We’re looking for a Full Stack/ Data Science Engineer who expects more from their career. It’s a chance to make accessible to clients the latest and best ready-to-use science products and/or software modules, helping Dunnhumby and its clients serve billions of customers worldwide

What we expect from you

  • Bachelor’s degree or higher in Mathematics, Economics, Applied Statistics, Computer Science, Physics, Engineering or related field.
  • Experience with and passion for building full-stack applications and an appetite for understanding and implementing ways to connect with various data science algorithms on the big data backend.
  • Frontend stack – Reactjs, Typescript, Redux, Cypress
  • Backend stack – Nodejs, Typescript, Prisma, Postgres, SQL, GCP, Linux, Docker
  • Good knowledge of SQL (joins, subqueries, etc) and optimisation techniques
  • Knowledge of general software design, architecture and best practices
  • To develop the front-end and back-end of a web app with strong focus on modularity, customisability, scalability, and maintainability.
  • Work with team to understand requirements for new features and design the software components. Input into re-engineering and design based on own expertise and implement advice from colleagues to resolve challenges.
  • To support with closing of issues (bugs) and support Dev Ops personnel during development, and to provide production support as per capacity
  • To support with the data modelling for resources, etc and suggets ways to standardize/unify the app/data model across various markets/clients.
  • Work with big data engineers to help with integration of features (web-to-big-data-powered-workflows/products) and with infra engineers to enhance the app/science platform

What you can expect from us

We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect.  Plus, thoughtful perks, like flexible working hours and your birthday off.

You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.

And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof.  We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. 

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.

For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)

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The Company
HQ: London
0 Employees
Year Founded: 1989

What We Do

Dunnhumby is a customer data platform that provides models and insights into how customers engage with retail and e-commerce spaces.

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