Role description

Job Summary:

The Senior Manager, Data Science will lead a team of data scientists to develop advanced analytical models and drive data-driven decision-making across the organization. This role requires a solid blend of technical expertise, strategic thinking, and leadership skills. The Senior Manager will collaborate with cross-functional teams to identify business opportunities, design and implement innovative data solutions, and contribute to the company’s overall strategic goals.

Key Responsibilities:

1. Leadership and Team Management:

- Lead, mentor, and develop a team of data scientists.
- Foster a culture of innovation, collaboration, and continuous learning.
- Set clear goals and performance expectations for the team.

1. Strategy and Vision:

- Define and implement the data science strategy aligned with the company’s objectives.
- Identify and prioritize data science projects that drive business value.
- Stay abreast of industry trends and emerging technologies to keep the organization at the forefront of data science.

1. Technical Expertise:

- Oversee the development and deployment of machine learning models and algorithms.
- Ensure best practices in data modeling, coding, and experimental design.
- Provide technical guidance on complex data science projects.

1. Collaboration and Communication:

- Work closely with business leaders to understand their needs and translate them into data science initiatives.
- Communicate findings and recommendations to both technical and non-technical stakeholders.
- Collaborate with data engineering, IT, and other departments to ensure data availability and integrity.

1. Project Management:

- Manage multiple data science projects,



ensuring timely and successful delivery.
- Allocate resources effectively and balance team workloads.
- Monitor project progress and make adjustments as needed.

1. Performance Measurement:

- Develop metrics to measure the impact and effectiveness of data science initiatives.
- Continuously evaluate and refine models and strategies based on performance data.
- Report on key performance indicators to senior management.

Qualifications:

Education:

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Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Master’s or Ph.D. preferred.

Experience:

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10+ years of experience in data science or a related field.

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3+ years in a leadership or managerial role within a data science team.

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Proven track record of delivering impactful data science solutions in a business context.

Technical Skills:

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Expertise in statistical analysis, machine learning, and predictive modeling.

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Proficiency in programming languages such as Python, R, or SQL.

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Proven experience / Subject Matter expert in one or more of the following:

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Causal modeling / experimentation

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Price elasticity / pricing models

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Forecasting / time-series models

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Optimization or classical ML algorithms

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Recommendation o

Experience with data visualization tools like Tableau, Power BI, or similar.

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Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure).

Soft Skills:

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Strong analytical and problem-solving abilities.

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Excellent communication and presentation skills.

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Ability to translate complex technical concepts into actionable business insights.

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Strong organizational and project management skills.

📌 Data Science Senior Manager (Bengaluru)
🏢 Tredence
📍 Bengaluru