Data Science Manager-MMM

PeopleStrong; India; Sur place; INR 4 000 000 - 7 000 000; Plein temps

Résumé du poste

PeopleStrong is seeking a Data Science Manager - MMM to lead high-impact analytics engagements and oversee a team of data scientists delivering Marketing Mix Modeling solutions.

This role combines econometric modeling with strong leadership and client management, guiding project scoping, model development, validation, and insights delivery to optimize marketing ROI. You will work with global clients across industries, foster innovation, and build scalable analytics pipelines.

Qualifications

• 8–12 years in advanced analytics with MMM.
• Experience leading cross-functional teams.
• Proven MMM project delivery for global clients.
• Strong econometric and statistical modeling skills.
• Proficient in Python and SQL.
• Excellent client-facing communication.

Responsabilités

• Lead and mentor a data science team on MMM projects.
• Oversee end-to-end MMM lifecycle from data prep to ROI.
• Provide hands-on technical oversight and model validation.
• Communicate insights to executive stakeholders.
• Drive innovation with causal inference and ML.
• Manage client communications and project scoping.

Connaissances

Marketing Mix Modeling

Team leadership

Python

SQL

Statistical modeling

Bayesian methods

Client communication

Data visualization

Outils

Tableau

Power BI

Python

SQL

Description du poste

Job Description

We are seeking a Data Science Manager - MMM to lead high-impact analytics engagements and oversee a team of data scientists delivering cutting-edge Marketing Mix Modeling (MMM) solutions. This role combines technical excellence in econometric modeling and advanced analytics with strong leadership and client management capabilities.

Key Responsibilities

• Lead, mentor, and manage a team of data scientists to deliver high-impact MMM and advanced analytics projects.
• Foster a collaborative, high-performance team culture focused on technical excellence, innovation, and continuous learning.
• Provide hands-on technical oversight, ensuring high-quality model development, validation, and actionable output.
• Support career development of team members through regular coaching, performance feedback, and skill-building opportunities.
• Act as a strategic advisor to senior client stakeholders, articulating the value of MMM and influencing data-driven decisions.
• Manage end-to-end client communications, including project scoping, milestone planning, insights delivery, and relationship growth.
• Oversee the complete MMM lifecycle—from data preparation to modeling, forecasting, and marketing ROI optimization.
• Drive innovation by integrating advanced methods such as causal inference and machine learning, while ensuring scalable, automated analytics pipelines.

Required Skills and Experience

• 8-12 years of experience in advanced analytics or data science, with significant hands-on expertise in Marketing Mix Modeling.
• Demonstrated experience leading cross-functional teams and managing direct reports in a data science/analytics function.
• Proven track record of delivering MMM projects for global clients across industries (e.g., CPG, Retail, BFSI, Tech).
• Strong statistical/econometric modeling skills using regression, time series, Bayesian, and hierarchical models.
• Advanced proficiency in Python with solid experience in SQL for data manipulation and extraction.
• Exceptional problem-solving abilities and experience working with large, complex datasets from multiple sources.
• Excellent communication and client-facing skills, with the ability to present complex insights to executive stakeholders and influence decision-making.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) and experience building client-ready dashboards is a plus.

Being a Mathemagician

• Embody MathCo's culture and way of working.
• Demonstrate ownership and strive for excellence in delivering results.
• Actively engage and contribute to initiatives fostering company growth.

Support diversity and appreciate different perspectives.