Job Specifications
My client is a global IT consultancy who are looking for Data Scientist to join a project,
The role is based in Heathrow 3 days per week and would also include European travel
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 modelling 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 (eg, to maximize impact and value realization)
Accountabilities
The Data Scientist has full-stack accountabilities across the full value chain of building an industrialized data-science software product:
o Understanding a business problem and its component processes end to end, and identifying opportunities to make decisions more optimally leveraging decision-support tooling
o Efficiently conducting analyses and visualizations to identify valuable opportunities for decision[1]support and to determine trade-offs between different potential feature implementations
o Prototyping advanced machine learning and optimization models to prove the value of a use case and approach (in Python)
o Delivering features to industrialize machine learning and optimization models in Python using best-practice software principles (eg, strict typing, classes, testing)
o Build automated, robust data cleaning pipelines that follow software best-practices (in Python)
o Implementing integrations between the core algorithm (machine-learning or optimization) and a workflow orchestration paradigm such as Dagster
o Implementing software in a cloud-based deployment pipeline with Continuous Integration/Continuous Deployment (CI/CD) principles
o Building logging, error handling, and automated tests (eg, unit tests, regression tests) to ensure the robustness of operationally critical decision-support products
o Deliver features to harden an algorithm against edge cases in the operation and in data
o Conduct analysis to quantify the adoption and value-capture from a decision- support product
o Engage with business stakeholders to collect requirements and get feedback
o Contribute to conversations on feature prioritisaion and roadmap, with an understanding of the trade-off between speed vs. long-term value
o Understand and integrate the product into existing business processes, and contribute to the development and adoption of new business processes leveraging a decision-support product
o Communicate feature and modelling 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:
o Using Git-versioning best practices for version control
o Contributing and reviewing pull-requests and product/technical documentation
o Giving input on prioritization, team process improvements, optimizing technology choices
o Working independently and giving predictability on delivery timelines
My core traits
Systems thinking
Detail oriented while understanding the big picture
Curious, self-motivated, proactive, and action-oriented
Creative and innovative
Resilient and flexible in light of changing priorities and approached
Data-driven
Pragmatic
Collaborative
A true believer in the power of using data to drive better decision making
A technologist, interested in keeping up with the latest and greatest in software development, optimization, and machine learning
Commitment to delivering business value
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 (eg seaborn)
Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (eg MLflow)
Experience with cloud-based ML tools (eg SageMaker), data and model versioning (eg DVC), CI/CD (eg GitHub Actions), workflow orchestration (eg Airflow/Dagster) and containerised solutions (eg 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 analy