Data Scientist

• Turn real business problems into analytical questions and model designs.
• Work with traders, risk managers, finance, digital, and data teams to understand how decisions are made.
• Build and test machine learning / statistical / optimization models and evaluate them with robust validation approaches.
• Create datasets, explainability outputs, and decision-support products (recommendations, alerts, dashboards, decision cards).
• Communicate results clearly, so non-technical stakeholders can trust and act on them.
• Typical projects include: regime-shift detection, price sensitivity/hedge analytics, forecasting supply/demand/inventory risk, and explainable tools for decision reviews.

Data Science Graduate Program

• Lead development of statistical and machine learning models to optimize performance
• Design and execute A/B/n experiments for measurable improvements
• Translate results into production-ready solutions
• Collaborate with cross-functional stakeholders to identify use cases
• Own the model lifecycle from ideation to performance monitoring
• Present findings to technical and non-technical audiences
• Contribute to data science practices and frameworks

Data Scientist – Medior

• Lead the development and evaluation of advanced search and generative AI systems
• Own complex problem areas end-to-end, drive methodological rigor in evaluation, and contribute to the technical direction of retrieval and RAG systems
• Play a leading role in the design and optimization of lexical, vector, and hybrid retrieval systems at scale
• Help architect and improve RAG pipelines, including retrieval strategies, prompt design, and system orchestration (e.g., LangGraph-based workflows)
• Drive experimentation with embeddings, re-ranking models, and retrieval architectures to significantly improve relevance and user outcomes
• Partner with engineering to ensure robust, scalable, and production-ready implementations
• Help define and evolve evaluation strategies for search and generative AI systems across products
• Contribute to responsible AI practices, including bias, fairness, and risk evaluation
• Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems
• Take ownership of projects from problem definition through experimentation and deployment

Senior Data Scientist

• Play a key role in transforming raw sensor data into valuable insights
• Design heuristics and algorithms that enrich this data in real time
• Develop models that generate actionable and personalized advice
• Involved in the development process: from data quality checks to deploying and maintaining prediction pipelines
• Work closely with Data Engineers to create deployable artifacts
• Interface directly with customers to gain understanding of their processes
• Work autonomously in a fast-moving environment with the ability to prioritize and solve customer needs

• Mine Unstructured Data: Use NLP (ClinicalBERT / BioBERT) to extract anxiety markers and procedural indicators from thousands of anonymized clinical notes.
• Feature Engineering: Clean and join complex longitudinal datasets including medication dosages (Infusion tables), vitals (Flowsheets), and recovery timestamps.
• Build the Model: Develop and validate an XGBoost classification model to output an "XR Suitability Score" with a target AUC-ROC of >0.75.

See all jobs on JobTailor

Data Science Graduate Program

Data Scientist – Medior

Senior Data Scientist

Senior Data Scientist

AI & Medical Data Science Internship