
Role Overview:
We are looking for a high-caliber Manager - Data Scientist to join our Mumbai-based team, where you will bridge the gap between complex data architecture and actionable business strategy. In this role, you will lead the end-to-end lifecycle of advanced analytical models, working closely with cross-functional product teams and senior stakeholders to solve high-impact business problems. You will be responsible for translating ambiguous business requirements into robust machine learning solutions, ensuring that our data-driven initiatives directly influence customer experience and bottom-line growth.
Key Responsibilities:
- Deploy scalable machine learning models to optimize business processes and improve predictive accuracy for our core product offerings.
- Lead the integration of Generative AI frameworks into existing workflows to automate content generation and enhance user personalization.
- Collaborate with engineering teams to implement MLOps best practices, ensuring seamless model deployment, monitoring, and lifecycle management.
- Translate complex statistical findings into intuitive data visualizations and executive-level reports to drive informed decision-making among stakeholders.
- Mentor team members on advanced data modeling techniques and Python-based development to foster a culture of technical excellence and continuous learning.
Required Skillset:
- Demonstrated proficiency in Python and its ecosystem for data science.
- Proven ability to apply statistical rigor and machine learning algorithms to solve real-world business challenges, supported by a strong foundation in data modeling.
- Exceptional communication skills with the ability to articulate technical concepts to non-technical stakeholders and influence cross-departmental strategy.
- Strong analytical mindset with a background in quantitative disciplines, such as Mathematics, Statistics, or Computer Science, from a top-tier institute.
- High degree of adaptability to a hybrid work environment in Mumbai, demonstrating the ability to collaborate effectively across both virtual and in-person team settings.
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