Data Science Senior Manager

Tredence

Bengaluru

On-site

INR 3,000,000 - 5,400,000

Full time

7 days ago
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Job summary

Tredence in Bengaluru seeks a Senior Manager, Data Science to lead a team of data scientists and develop advanced analytical models that guide data-driven decisions across the organization.

You'll collaborate with cross-functional teams, design innovative data solutions, and contribute to the company's strategic goals through rigorous modeling and stakeholder communication.

Qualifications

  • 10+ years of experience in data science or a related field.
  • 3+ years in a leadership or managerial role within a data science team.
  • Proven track record of delivering impactful data science solutions in a business context.

Responsibilities

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

Skills

SQL
Python
Statistics
Machine Learning
Deep Learning
Data Science
Forecasting
Causal Inference
Recommendation
Pricing
Price Elasticity
Revenue Growth Management

Education

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

Tools

Hadoop
Spark
AWS
Azure
Tableau
Power BI

Job 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 strong 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
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.
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.
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.
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.
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.
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
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Master's or Ph.D. preferred.
Experience
  • 10+ years of experience in data science or a related field.
  • 3+ years in a leadership or managerial role within a data science team.
  • Proven track record of delivering impactful data science solutions in a business context.
Technical Skills
  • Expertise in statistical analysis, machine learning, and predictive modeling.
  • Proficiency in programming languages such as Python, R, or SQL.
  • Proven experience / Subject Matter expert in one or more of the following:
  • Causal modeling / experimentation
  • Price elasticity / pricing models
  • Forecasting / time-series models
  • Optimization or classical ML algorithms
  • Recommendation
  • Experience with data visualization tools like Tableau, Power BI, or similar.
  • Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure).
Soft Skills
  • Strong analytical and problem-solving abilities.
  • Excellent communication and presentation skills.
  • Ability to translate complex technical concepts into actionable business insights.
  • Strong organizational and project management skills.
Required Skills
  • Sql
  • Python
  • Statistics
  • Machine Learning
  • Deep Learning
  • Data Science
  • Forecasting
  • Causal Inference
  • Recommendation
  • Pricing
  • Price Elasticity
  • Revenue Growth Management
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