
Manager - Data Science
2 days ago
Role & responsibilities :
Leadership & Strategy:
- Lead and manage a team of 20 Data Scientists (DS), ensuring high performance and continuous growth
- Define and implement the companys data science vision and strategy
- Work closely with global business leaders to identify opportunities where data science can drive business value
- Stay up to date with emerging trends in AI, ML, and advanced data analytics to drive innovation.
Ensure all agreed Key Performance Indicators (KPIs) are met in line with performance agreements, maintaining high
standards of operational efficiency
Data Science:
- Develop and deploy machine learning models, statistical algorithms and predictive analytics solutions.
- Ensure the scalability, reliability and efficiency of data science models and pipelines.
- Collaborate with engineering and data teams to improve data quality, availability and infrastructure
- Participate in global meets & workshops to review & develop strong process and strategy for DS services in India
- Utilize advanced analytics to solve complex business problems and improve decision-making
Stakeholder Management:
- Partner with cross-functional teams (engineering, operations) to translate business needs into data-driven
solutions
- Communicate insights and recommendations to both technical and non-technical stakeholders
- Develop data-driven strategies to optimize customer experience, revenue and operational efficiency
- Exhibit very strong local and global stakeholders management skill
- Support in developing proactive proposals and solutions to internal and external stakeholders.
Team Development & Mentorship:
- Recruit, train and mentor Data Scientists, Data Engineers and AI platform engineers, fostering a culture of innovation.
- Support HR partner with building hiring strategy for the niched skills
- Conduct performance evaluations, provide feedback and set career development plans for the team members
- Encourage best practices in coding, model deployment and data governance.
Desired candidate profile :
Bachelors or Masters or PhD in Data Science, Computer Science, Statistics, Mathematics or a related field.
Technical Skills:
- 10-15 years of total experience with min 5 yrs in data science, analytics, AI/Deep Learning, NLP and Generative AI.
- Strong proficiency in Python, R, SQL and cloud platforms (AWS, GCP, or Azure)
- Expertise in Machine Learning frameworks (TensorFlow, PyTorch, Scikit-learn)
- Experience with big data technologies (Spark, Hadoop, Databricks) and data engineering concepts.
- Solid understanding of statistics, probability and optimization techniques.
- Experience with MLOps, model deployment and productionizing ML models.
- Industry experience in Aviation, Automotive, Finance, Healthcare, Retail or any IT Technology based domain.
Leadership & Business Acumen:
- • Proven experience in leading and managing data science teams.
- • Ability to translate business problems into data science solutions.
- • Strong communication and stakeholder management skills.
- • Experience in budget planning, resource allocation and project management.
- • Proficiency in Risk assessment and mitigation planning.
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