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Senior Research Data Scientist

TN United Kingdom

London

On-site

GBP 40,000 - 80,000

Full time

28 days ago

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Job summary

An innovative firm is seeking a talented Research Data Scientist to enhance its world-class science capabilities. This role offers the opportunity to work with a market leader in applying machine learning and statistical techniques to solve complex business problems. You will collaborate with passionate professionals to create effective science solutions, optimizing product offerings and enhancing customer experiences. With a focus on flexibility and inclusion, this position allows you to balance personal commitments while contributing to impactful projects. Join a dynamic team that values diversity and personal growth, while pushing the boundaries of data science.

Benefits

Flexible working hours
Birthday off
Investment in cutting-edge technology
Diversity and inclusion initiatives

Qualifications

  • Master's degree in a relevant field and experience with machine learning techniques.
  • Proficiency in Python and ability to handle large data volumes.

Responsibilities

  • Create science-based solutions and apply machine learning techniques on client data.
  • Perform exploratory data analysis and ensure project smoothness.

Skills

Machine Learning Techniques
Data Analysis
Statistical Techniques
Programming in Python
Data Visualization
Natural Language Processing

Education

Master's degree in Computer Science
PhD in related field

Tools

Python
Spark
Hadoop
SQL
Pandas
scikit-learn

Job description

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We’re looking for a talented Research Data Scientist who expects more from their career. It’s a chance to extend and improve dunnhumby’s world class science capabilities. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers. Joining our team, you’ll work with world class and passionate people to apply machine learning and statistical techniques to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll have the opportunity to present results to a variety of internal stakeholders.

You will apply these techniques and algorithms to create dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will be focussed on ensuring the right product is in the hands of the customer, stretching from how category needs vary across stores and online, identifying new and growing needs, optimising the mix of products, predicting the impact of changes and maximising the in-store experience.

What you'll be doing:

  1. Create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members.
  2. Pick up new machine learning approaches, such as regularised regression, clustering or tree-based ensembles, graph-based approaches, natural language processing and neural network techniques and apply them on client data.
  3. Perform exploratory data analysis to characterise and visualise datasets.
  4. Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules.
  5. Help identify new opportunities within the Data Science space for future dunnhumby solutions.
  6. Implement advice from colleagues to resolve challenges.
  7. Follow Quality Assurance processes, ways of working and meet coding standards.
  8. Ensure smooth running of your projects, working with senior team members for direction.
  9. Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Who you’ll get to work with:

Within dunnhumby you’ll primarily work with:

  1. Applied and Research Data Scientist teams
  2. Data Science Engineering teams
  3. Product and Client teams where required

What you'll need:

  1. Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
  2. Experience with machine learning techniques such as regularised regression, clustering or tree-based ensembles, and the ability to implement them through libraries.
  3. Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL.
  4. Experience with or ability to quickly learn open-source software including machine learning packages, such as Pandas and scikit-learn, along with data visualisation technologies.
  5. A willingness to present your work to both technical and non-technical audience and to contribute to the wider data science community.

A plus if you also have:

  1. PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
  2. Experience in retail sector.

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 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. For an informal and confidential chat please contact to discuss how we can meet your needs.

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.

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