Lead Data Scientist
- Optum
- 5 - 9 years
- Bengaluru
- 7 months ago
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Job Description
Role Summary: As a Lead Data Scientist, you will drive strategic data initiatives, lead advanced analytics projects, and mentor a team of data scientists. You will collaborate cross-functionally to translate business problems into data-driven solutions, leveraging machine learning, statistical modeling, and big data technologies. Key Responsibilities: Leadership & Strategy: Lead end-to-end data science projects from ideation to deployment.Define and drive the data science roadmap aligned with business goals.
Mentor junior data scientists and foster a culture of innovation and collaboration.
Technical Expertise: Design and implement predictive models, optimization algorithms, and statistical analyses.
Develop scalable machine learning pipelines and deploy models in production environments.
Perform exploratory data analysis and feature engineering on large datasets.
Collaboration & Communication: Work closely with product, engineering, and business stakeholders to identify opportunities and deliver insights.
Communicate complex analytical concepts to non-technical audiences effectively.
Present findings and recommendations to senior leadership.
Tools & Technologies: Proficiency in Python/R, SQL, Spark, and cloud platforms (AWS/GCP/Azure).
Experience with ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
Familiarity with data visualization tools (e.g., Tableau, Power BI, Plotly).
ML Ops Monitoring and Observability tool development
Preferred Qualifications: 1. Masters/ M tech / Ph.D. with a strong research background in machine learning or statistical modeling.
2. Certifications in cloud platforms (AWS Certified Machine Learning, Google Professional Data Engineer, etc.).
Job Classification
Industry: RetailFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full timeContact Details:
Company: OptumLocation(s): Bengaluru
Keyskills: python machine learning sql r statistical modeling advanced analytics algorithms scikit-learn bi big data technologies predictive microsoft azure power bi cloud platforms tensorflow tableau data science spark gcp pytorch data visualization aws ml
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