Sr. Data Scientist

Sr. Scientist — Data & AI/ML (12 Yrs of Experience) Client: Direct C2C Rate: $Open/hr on C2C Location: Remote (NY/NJ) Department: Data Science / Data & AI We need 12+ Years of exp candidates for this role. About the Role We are seeking a Data Scientist to frame problems, run experiments, and develop models that turn data into actionable insight. Partnering with our Solution Architects, AI/ML Engineers, and stakeholders, you'll work from the earliest discovery conversations through analysis and modeling — helping shape what gets built and proving out what works. The ideal candidate is intellectually curious and pragmatic: someone who can ramp up quickly on a new domain, ask sharp questions during discovery, and move from hypothesis to validated insight fast in an iterative, rapid-development environment. You're equally comfortable digging into messy data, designing a rigorous experiment, and explaining results clearly to a non-technical audience. What You'll Do • 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. What You Bring Required Qualifications • 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. Technical Skills • 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. Preferred Qualifications • 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.