Data Scientist in Preston

We have an exciting contract job opportunity for a Data Scientist to join our leading airline client.

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

Contract: 12 months (high potential to extend further)

Location: Heathrow

Hybrid: 2 to 3 days onsite

Pay: Flexible daily rate (inside IR35)

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.

Accountabilities:

• Understanding a business problem and its component processes end to end, and identifying opportunities to make decisions more optimally leveraging decision-support tooling.
• Efficiently conducting analyses and visualizations to identify valuable opportunities for decision-support and to determine trade-offs between different potential feature implementations.
• Prototyping advanced machine learning and optimization models to prove the value of a use case and approach (in Python).
• Delivering features to industrialize machine learning and optimization models in Python using best-practice software principles (e.g., strict typing, classes, testing).
• Building automated, robust data cleaning pipelines that follow software best-practices (in Python).
• Implementing integrations between the core algorithm (machine-learning or optimization) and a workflow orchestration paradigm such as Dagster.
• Implementing software in a cloud-based deployment pipeline with Continuous Integration / Continuous Deployment (CI/CD) principles.
• Building logging, error handling, and automated tests (e.g., unit tests, regression tests) to ensure the robustness of operationally critical decision-support products.
• Delivering features to harden an algorithm against edge cases in the operation and in data.
• Conducting analysis to quantify the adoption and value-capture from a decision-support product.
• Engaging with business stakeholders to collect requirements and get feedback.
• Contributing to conversations on feature prioritisation and roadmap, with an understanding of the trade-off between speed vs. long-term value.
• Understanding and integrating the product into existing business processes, and contributing to the development and adoption of new business processes leveraging a decision-support product.
• Communicating feature and modeling approach, trade-offs, and results with the internal team and business stakeholders.

The Data Scientist is also accountable for ways of working fit for an Agile cross-functional development squad, including:

• Using Git-versioning best practices for version control.
• Contributing and reviewing pull-requests and product/technical documentation.
• Giving input on prioritization, team process improvements, optimizing technology choices.
• Working independently and giving predictability on delivery timelines.

Skills/capabilities:

• Strong knowledge of either machine learning and optimization techniques, including 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 PowerPoint.

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 optimization 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.

Qualifications/experience:

• Master’s degree or greater in data science, ML, or operational research, or 2+ years of highly relevant industry experience (required).
• Extensive working on production ML or optimization software products at scale (required).
• Experience in developing industrialized software, especially data science or machine learning software products (preferred).
• Experience in relevant business domains (transportation, airlines, operations, network problems) (preferred).

Next Steps: Once you’ve applied, one of our friendly recruitment consultants will give you a call and talk you through the screening process. If your application is successful, you’ll be involved in a live virtual interview with one of our client’s hiring managers to get to know you better. We look forward to speaking to you!