Senior Data Scientist – Job Description
We are seeking a Senior Data Scientist with deep experience translating business requirements into technical specifications, manipulating large datasets, and supporting a broad range of data initiatives for our clients. Our Data Scientists design, enhance, and support data services and analytics capabilities used by our clients and their customers. They work closely with business partners and Data Engineering/Analytics teams to understand data meaning and intent, provide analytical insights, and ensure data designs and solutions align with defined standards.
About You
You are a data professional with strong hands-on technical skills and exceptional attention to detail. You thrive in collaborative environments, working with large-scale datasets and developing advanced analytics solutions. You are a problem solver who is passionate about transforming data into meaningful business impact.
Responsibilities
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Client leadership & project delivery: Independently engage with client leadership, lead project meetings to align on scope and timelines, provide analytical support across the portfolio, and ensure smooth, timely delivery; perform additional duties as needed.
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Modeling, experimentation & optimization: Design and deploy analytical models (forecasting, classification/regression, segmentation), conduct A/B testing and causal analyses, and develop optimization solutions (linear, mixed-integer, multi-objective). Ensure rigorous validation with diagnostics, monitoring, and complete documentation.
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Analysis & storytelling: Execute advanced data analyses; interpret and synthesize findings; present clear insights to internal and external stakeholders; prepare executive-ready presentations and visualizations using Tableau and Power BI.
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Requirements & business rules: Partner with business and engineering teams to elicit requirements, define and document business rules, and translate needs into technical specifications and user-facing documentation.
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Data integration & quality: Integrate data from diverse sources; monitor and validate data flows; develop or enhance data-quality reporting; conduct root-cause analysis; test database changes prior to release; use Databricks for scalable data processing.
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MLOps & deployment: Collaborate with engineering teams to implement MLOps practices including MLflow pipelines, model deployment, monitoring, and end-to-end lifecycle management.
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Version control & collaboration: Use Git/GitLab for code management, reproducibility, and collaborative development with engineering teams.
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Data governance & compliance: Ensure adherence to data governance, privacy, compliance, and regulatory frameworks.
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Metrics & communication: Build new metrics and KPI reports that drive business decisions; communicate effectively with business and technical leads and respond appropriately to sensitive inquiries.
Qualifications / Skills
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Experience: 5–7+ years of hands-on analytics including predictive modeling, experimentation (A/B testing), and optimization; 3–5 years presenting analyses to management and partnering with business/technical stakeholders; demonstrated leadership of multi-member client projects; expertise in experimental design, model diagnostics, and monitoring with clear, reproducible documentation.
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Technical (required): Advanced SQL and Python; ability to query, manipulate, and interpret data from databases/data warehouses; strong Excel and PowerPoint skills; hands-on experience with Databricks for large-scale data processing and machine learning workflows; proficiency with Tableau and/or Power BI; experience with Git/GitLab; understanding of data governance, privacy, and compliance standards.
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Technical (preferred): Proficiency with SAS and R; familiarity with automotive/VIN data; experience working with large/complex data structures; understanding of MDM concepts; exposure to MLOps practices.
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Data quality & problem solving: Proven experience diagnosing and resolving data-quality issues across multiple platforms.
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Communication: Excellent interpersonal, verbal, and written communication skills; ability to work with both business and technical audiences and respond effectively to sensitive or complex inquiries.
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Education: BA/BS in Computer Science, MIS, Statistics, Mathematics, Marketing Research, or a related quantitative field (or equivalent practical experience).
