Data Scientist - AI

Job Description:

Data Scientist

Inside IR35

Hybrid London

This role is responsible for developing industrialised optimisation and machine learning models as part of a full-stack product squad that delivers operations decision-support software.

Scope

As a key member of a product squad and reporting to the Lead Product Data Scientist, a Data Scientist will develop data pipelines, machine learning models, and complex optimization models in the ODS software product suite.

The Data Scientist is in charge of modeling and robust implementation of features contributing to an operations decision-support product.

In developing a product's core algorithm, the full-stack Data Scientist role will ensure that their features integrate seamlessly into the product's technical stack (data ingestion, user interface, orchestration) as well as the business process and use case (e.g., to maximize impact and value realisation)

Skills/capabilities

• Strong knowledge of either machine learning and optimization techniques, incl. supervised (regression, tree methods, etc.), unsupervised (clustering) learning, and operations research (linear, mixed integer programming, heuristics)
• Fluent in Python(required) and other programming languages (preferred)with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobi etc.) to solve real-life problems and visualise the outcomes (e.g. seaborn)
• Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g. MLflow)
• Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) nice to have
• Experience in code testing (unit, integration, end-to-end tests)
• Strong data engineering skills in SQL and Python
• Proficient in use of Microsoft Office, including advanced Excel and PowerpointSkills
• Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights
• Understanding of the trade-offs of different data science, machine learning, and optimisation approaches, and ability to intelligently select which are the best candidates to solve a particular business problem
• Able to structure business and technical problems, identify trade-offs, and propose solutions
• Communication of advanced technical concepts to audiences with varying levels of technical skills
• Managing priorities and timelines to deliver features in a timely manner that meet business requirements
• Collaborative team-working, giving and receiving feedback, and always seeking to improve team processes

£540.00 / day

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