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Applied Data Scientist
Not specifiedFull-timeData ScienceFinTechEnterprise Software
Build and deploy models that turn financial transaction data into customer insights. Work with Product and Engineering from problem evaluation through production and ongoing improvement.
Responsibilities
- Frame analytical problems, review existing approaches, and assess available evidence and data
- Engineer features and design models using suitable machine learning, deep learning, LLM, or agentic approaches
- Prepare model specifications, evaluation evidence, and risk documentation for regulated production use, and support reviews
- Partner with Engineering to take solutions from proof of concept to live service, including integration and controlled rollout
- Monitor model performance, drift, and business KPIs in production and improve models based on observed results
Requirements
- At least 2 years of hands-on data science experience in a product environment
- Strong Python skills, including Pandas, NumPy, scikit-learn, and PyTorch
- Experience with tabular machine learning, feature engineering, gradient-boosted trees, and model evaluation
- Hands-on experience building GenAI or LLM applications, including RAG, prompt engineering, and evaluation
- Experience building agentic systems with tool use, multi-step workflows, and orchestration
- Clear technical writing and ability to explain models to non-technical audiences
Nice to have
- FinTech or banking experience
- Transformer fine-tuning and production inference
- Experience launching and monitoring production models
- AWS or Azure experience