Data Scientist

YOUR ROLE AS A: Data Scientist

WHAT YOU’LL CHAMPION

You will improve models and algorithms to further optimize business outcomes. As a Data Scientist, you will work across the following areas:

• Exploratory analysis: use data to suggest and prove hypotheses.
• Modeling: built optimization / predictive / statistical models to learn from data and estimate the unknowns.
• Data operations: query data, deploy models and automate pipelines in cloud.
• Experience with common data science toolkits, programming languages, visualisation tools and SQL/NoSQL databases.
• Good applied statistical knowledge with emphasis in business and finance related statistical distributions, statistical testing, modeling, regression analysis.
• Experience with distributed computing platforms and open‑source tools and libraries.
• Familiar or prone to adopt design thinking methods.
• Able to work under pressure and change, and balance among speed, reliability, interpretability.
• Good working knowledge of productivity tools such as G Suite, Git, Jira, Confluence.
• Experience with code versioning, code review and documentation.

WHO YOU ARE

• BS/MS/PhD in a Business, IT, Mathematics, Science or Engineering discipline.
• Up to 4 years relevant experience beyond first degree.

Machine Learning

• 2–5 years building production ML systems — beyond notebooks and Kaggle competitions.
• Solid understanding of machine learning algorithms — XGBoost, LightGBM, neural networks, decision trees — with a clear grasp of why you tuned what you tuned.
• Strong Python and hands‑on experience with ML frameworks such as scikit‑learn, TensorFlow, or PyTorch.
• Demonstrable understanding of forecasting and regression pitfalls — lag feature leakage, target leakage in cross‑validation, high‑cardinality categorical handling, and the trade‑offs between MAE, MAPE, and RMSE.
• Ability to interpret models — SHAP, partial dependence, residual diagnostics — and explain results to non‑technical stakeholders without dumbing them down.
• Hands‑on Google Cloud Platform experience, particularly BigQuery (window functions, partitioning, cost‑aware SQL) and Vertex AI (training jobs, model registry, endpoints, pipelines).
• Nice‑to‑have: deep learning for tabular and time‑series problems (TFT, N‑BETS, NeuralProphet, TabPFN, Chronos); AutoML tooling such as PyCaret for rapid baselining.

Algorithm Engineering

• Strong ability to implement, improve, and deploy ML and mathematical models in Python (Golang a plus for performance‑critical services).
• Experience productionizing models end‑to‑end — from SQL feature pipelines to deployed serving endpoints — on GCP using Vertex AI and BigQuery.
• Conduct systems tests for security, performance, and availability of deployed models.
• Develop and maintain design documentation, error analysis runbooks, and troubleshooting guides.
• Git‑based workflows, CI/CD discipline, and code review hygiene.
• Monitoring discipline — drift detection, data quality checks, model performance tracking in production.
• Nice‑to‑have: experience with LLM‑based or agentic tooling (LangGraph, MCP servers, prompt engineering for structured outputs, eval harnesses for LLM systems).

WHAT YOU’LL ENJOY

• Physical Wellbeing: key medical and insurance benefits, maternity expenses, flexible work arrangement, and health and fitness amenities.
• Emotional Wellbeing: paid time off, wellness programmes, and childcare amenities.
• Financial Wellbeing: resources relating to financial, personal skills and career growth programmes.
• Allstars Specials: free flights, unlimited discounted flights, and exclusive discounts with partners.