Data Scientist

Job Description:- 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, gurobietc.) 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 Skills • 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, and always seeking to improve team processes Qualifications/experience • Master’s degree or greater in data science, ML, or operational research, or 2+ years of highly relevant industry experience(required) • 0-2 years 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) Key interfaces • Lead Product Data Scientist • Other Data Scientists • Business stakeholders and users • Software engineers (front-end, back-end, DevOps, data engineers) • Product & change managers • BA Digital teams (e.g., architects, application support managers) • External partners and third parties, as required • ODS Leadership (Head of Data & Analytics, Head of iOps& Optimisation, Director of ODS) • Key performance indicators • Model accuracy, performance, and runtime (precision, recall, accuracy) • Time to develop and deploy features and models • Data ingestion & processing efficiency and robustness • Code quality and robustness (e.g., unit test coverage) • Collaboration and cross-functional teamwork