Senior Data Scientist

Senior Data Scientist As Senior Data Scientist, you drive end-to-end ML solutions that deliver mission and business impact. You'll lead modeling strategy, mentor teammates, and partner with engineering, product, and mission stakeholders to translate analytics into actionable outcomes. You will tackle challenging problems with advanced ML techniques, ensure reliable and explainable models, and help shape the AI & Data Exploitation Practice. This is a hands-on, leadership-heavy role at a mission-driven company. Responsibilities Lead end-to-end development of predictive and analytical models, from problem framing to evaluation Architect and implement advanced ML techniques (ensembles, deep learning, NLP, time-series, anomaly detection) Conduct diagnostics, error analysis, and explainability studies for reliability and fairness Collaborate with Data Engineers and MLOps/LLMOps to operationalize models (pipelines, monitoring, retraining) Translate model outputs into clear insights for technical and non-technical audiences Partner with product, UX, and domain SMEs to define requirements and apply human-centered design Lead experimentation cycles to assess new approaches and data sources Ensure reproducible work via documentation, code reviews, version control, and experiment tracking Mentor associate and mid-level Data Scientists on techniques and project execution Stay current on ML techniques and cloud-native tools to shape team strategy and capabilities Key requirements 8+ years of data science experience with a Bachelor's degree or 6+ years with a Master's degree 5+ years designing, building, deploying ML or advanced analytics solutions Strong Python proficiency with Pandas, NumPy, scikit-learn; hands-on with PyTorch, TensorFlow, or XGBoost Experience leading data science workstreams and mentoring SQL experience and handling structured, semi-structured, or unstructured data at scale Familiarity with AWS, Azure, GCP and ML platforms (Databricks, SageMaker, Azure ML Studio) Strong foundation in statistics, experimental design, and model validation Excellent communication for explaining technical concepts to non-technical audiences Experience collaborating with product teams, engineers, and mission stakeholders Understanding of responsible AI: fairness, explainability, bias mitigation, reproducibility Preferred certifications: AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer, Databricks ML Steampunk.com