Note: The job is a remote job and is open to candidates in USA. MethodHub is seeking a Senior Data Scientist to frame problems, run experiments, and develop models that turn data into actionable insights. The role involves collaborating with Solution Architects, AI/ML Engineers, and stakeholders to analyze and model data, ensuring that findings are communicated effectively to both technical and non-technical audiences.
Responsibilities
- Frame business problems as analytical and ML problems , defining hypotheses, success metrics, and the right modeling approach
- Engage proactively during discovery , asking incisive questions, assessing data readiness, and identifying opportunities and risks early
- Perform exploratory data analysis to understand data quality, distributions, relationships, and feasibility before modeling
- Design and run experiments (A/B tests, statistical analyses) with appropriate rigor, and interpret results to drive decisions
- Develop, validate, and iterate on models — from statistical and classical ML approaches through to modern AI/GenAI techniques where appropriate
- Jumpstart contributions immediately by ramping quickly on new domains and datasets and delivering early, meaningful analysis
- Support rapid, iterative development — prototype quickly, validate assumptions, and partner with engineers to move promising work toward production
- Communicate findings clearly through visualizations, narratives, and recommendations tailored to technical and business audiences
- Collaborate across the team with architects, engineers, and stakeholders to keep analysis aligned with evolving goals
- Champion rigor and responsible AI — sound methodology, reproducibility, fairness, and clear articulation of assumptions and limitations
Skills
- 5+ years of experience applying data science and machine learning to real-world problems
- Strong foundation in statistics, experimental design, and machine learning methods
- Proficiency in Python (and/or R) and SQL, with experience in common data science libraries
- Hands-on experience with the modeling lifecycle: problem framing, EDA, feature engineering, model development, and evaluation
- Proven ability to ramp quickly and deliver insight in fast-moving, ambiguous environments
- Excellent communication and data storytelling skills, including the ability to explain complex results simply
- Authorized to work in the United States
- Languages & libraries: Python (pandas, NumPy, scikit-learn), SQL; R a plus
- ML & statistics: regression, classification, clustering, time series, hypothesis testing, experimental design
- Visualization: tools such as matplotlib, seaborn, Plotly, Tableau, or Power BI
- Platforms: experience with cloud data/ML environments (AWS, Azure, GCP, Databricks) and notebooks
- GenAI (plus): familiarity with LLMs, embeddings, and RAG approaches for analytical use cases
- Experience in a consulting or client-facing delivery environment
- Advanced degree in a quantitative field (Statistics, CS, Math, Economics, or similar) or equivalent experience
- Experience with experiment tracking (MLflow, Weights & Biases) and collaborating with engineers to productionize models
- Domain experience relevant to our clients
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