Job Description:
Senior Data Scientist driving end-to-end data science initiatives and advanced analytics in B2B sector, partnering cross-functionally with data science, engineering, and business stakeholders.
Core Responsibilities:
1. Data Science & Advanced Analytics:
Design, build, validate, and deploy sophisticated statistical and machine learning models in Databricks environment
Develop hypothesis-driven insights for executive leadership using large, multi-source datasets.
Conduct deep-dive analytics across the customer lifecycle (segmentation, behavior, performance trends)
Translate analytical findings into business-ready narratives and actionable recommendations.
Support and validate inputs for dashboard and performance tracking frameworks.
2. Project Leadership:
Lead end-to-end data science model development (problem framing → modeling → validation → insight delivery), ensuring measurable business impact.
Own model migration of legacy workflows to model data platforms(Databricks) enabling scalable, production-ready model development
Drive executive presentations, business reviews, and working sessions while managing milestones, timelines, and stakeholder alignment across workstreams.
Act as primary analytics liaison across internal data science and engineering teams to ensure seamless collaboration and deployment.
Ensure analytical solutions are scalable, reproducible, and aligned with governance standards within enterprise data environments.
Skills Required:
Technical:
Expert in Python (advanced analytics & ML)
Expert in SQL (large-scale data querying & transformation)
Intermediate in Alteryx (legacy workflow understanding & migration)
Intermediate in Databricks (ML engineering, notebook workflows, model deployment)
Functional:
Deep understanding of B2B sales, customer and market insights
Hypothesis-driven problem solving
Executive storytelling & insight synthesis
End-to-end project ownership
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