Manager, Data Science

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

We are Brainlabs the High-Performance media agency on a mission to become the worlds biggest and best independent media agency. We plan and buy media that delivers profitable and sustained business impact. And whats our formula Superteams of Brainlabbers fueled by data and enabled by technology.

Brainlabs has always been a culture-first fact from the very beginnings of the agency a set of shared principles philosophies and values was documented in The Brainlabs Handbook helping us create our unique culture.

As with everything here we always seek to adapt and improve so The Brainlabs Handbook has been fine-tuned to become The Brainlabs Culture Code.

This Culture Code consists of 12 codes that talk to what it means to be a Brainlabber. Its a joint commitment to continuous development and creating a company that we can all be proud of where Brainlabbers can turn up to do great work make great friends and win together.

You can read The Brainlabs Culture Code in full here.

So tell me about the company

Brainlabs is culture-first. Youve probably heard other companies describe themselves as people clients or profit first but we see people clients and profit as the building blocks of our ecosystem. Culture powers all three and we know that when the ecosystem is balanced we all win! Thats why the culture we cultivate is a culture of winning together.

To learn more about what its like to be a Brainlabber check out our culture code.

What you do

Project Execution & Delivery: Own end-to-end data science work from problem definition and data preparation to model development and final delivery. Plan milestones track progress manage risks and ensure timelines and quality across multiple projects.
Leadership & Ownership: Independently take ownership of projects drive technical and delivery decisions and grow into a strong lead role with minimal supervision.
Team Scaling & Management: Scale project delivery through a team by delegating tasks reviewing outputs providing clear direction and ensuring consistent execution standards.
Machine Learning & Advanced Analytics: Design build and review machine learning models including regression classification clustering NLP basic deep learning and applied LLM use cases aligned to business needs.
Marketing Mix Modeling (MMM): Lead Bayesian Marketing Mix Modeling using Meridian Robyn and PyMC. Review data inputs assumptions transformations and validation steps to ensure reliable outcomes.
Marketing & Attribution Analytics: Guide multi-touch attribution incrementality testing spend optimization lead scoring market basket analysis and CLTV use cases.
Causal Inference & Experimentation: Lead A/B testing uplift modeling and statistical analysis. Ensure correct experiment design execution and interpretation.
Demand Forecasting & Optimization: Oversee demand forecasting considering seasonality trends and external factors. Support price checks and simple optimization analysis.
MLOps & Production Readiness: Oversee model deployment retraining workflows CI/CD pipelines and monitoring. Ensure models are production-ready and reliable.
Cloud & Data Engineering: Use GCP AWS or Azure to run scalable machine learning workloads. Review data pipelines storage and processing for efficiency and reliability.
Python Programming: Strong hands-on experience with Python including pandas NumPy and scikit-learn with basic exposure to TensorFlow or PyTorch.
SQL & Data Warehousing: Strong experience with SQL and data warehouses such as BigQuery Snowflake or Redshift for data extraction and analysis.
Business Communication: Translate technical work into clear business recommendations build ROI views and present insights to senior and non-technical stakeholders.
Process & Governance: Enforce standard workflows naming conventions documentation and data handling practices across projects.
Continuous Learning & Team Development: Stay updated on relevant ML MLOps and cloud tools. Support learning and growth of team members.
Marketing & Advertising Knowledge: Strong understanding of marketing and advertising KPIs and how data science outputs support decision-making.
Ranking & Recommendation Systems: Exposure to ranking or basic recommendation system use cases is a plus.

Who you are

Python Programming (46 years): Strong coding skills using pandas NumPy and scikit-learn with basic experience in TensorFlow or PyTorch.
Machine Learning & LLMs (46 years): Hands-on experience with core ML techniques simple deep learning models and applied LLM usage in business projects.
SQL & Data Warehousing (45 years): Experience working with BigQuery Snowflake or Redshift for data extraction joins and analysis.
MLOps & CI/CD (34 years): Experience with Docker Kubernetes basics MLflow Airflow and running and monitoring ML pipelines.
Marketing & Attribution Modeling (34 years): Strong base in MMM inputs causal checks attribution logic and model validation.
Marketing Mix Modelling: MMM (46 years): Hands-on experience with Meridian Robyn and PyMC-based MMM frameworks.
Marketing Analytics Domain (46 years): Experience working on use cases such as spend optimization lead scoring MTA market basket analysis CLTV analysis and incrementality lift testing.
Cloud Platforms (34 years): Experience running and managing machine learning workloads on GCP AWS or Azure.
Technical Leadership (23 years): Experience leading data science workstreams reviewing technical outputs and guiding solution design.
People Management & Delivery Ownership (23 years): Experience managing and mentoring 13 team members owning delivery timelines and scaling execution through a team

Preferred Skills

Understanding of advertising and marketing KPIs
Experience with ranking or basic recommendation systems

Education

Bachelors or Masters degree in a quantitative field (Statistics Mathematics Computer Science or related field).

What happens next

We know searching for a job is tough and that you want to find the best career and employer for you. We also want to ensure that this position is the best fit for both you and us. Therefore you will participate in a comprehensive interview process that includes skills interviews with our team. The goal of this process is to allow you to get to know us as we learn more about you.

Brainlabs actively seeks and encourages applications from candidates with diverse backgrounds and identities.

Thank you for your interest in Brainlabs! We look forward to getting to know you!

What happens next

Brainlabs actively seeks and encourages applications from candidates with diverse backgrounds and identities. We are proud to be an equal opportunity workplace: we are committed to equal opportunity for all applicants and employees regardless of age disability sex gender reassignment sexual orientation pregnancy and maternity race religion or belief and marriage and civil partnerships. If you have a disability or special need that requires accommodation during the application process please let us know!

Please note that we will never ask you to transfer cash or make any other payment to us in order to apply for a role or to work for Brainlabs. Any such asks are fraudulent and should be reported to the appropriate authorities in your area.

Required Experience:

Manager

As with everything here we always seek to adapt and improve so The Brainlabs Handbook has been fine-tuned to become The Brainlabs Culture Code.

You can read The Brainlabs Culture Code in full here.

So tell me about the company

To learn more about what its like to be a Brainlabber check out our culture code.

What you do

Project Execution & Delivery: Own end-to-end data science work from problem definition and data preparation to model development and final delivery. Plan milestones track progress manage risks and ensure timelines and quality across multiple projects.
Leadership & Ownership: Independently take ownership of projects drive technical and delivery decisions and grow into a strong lead role with minimal supervision.
Team Scaling & Management: Scale project delivery through a team by delegating tasks reviewing outputs providing clear direction and ensuring consistent execution standards.
Machine Learning & Advanced Analytics: Design build and review machine learning models including regression classification clustering NLP basic deep learning and applied LLM use cases aligned to business needs.
Marketing Mix Modeling (MMM): Lead Bayesian Marketing Mix Modeling using Meridian Robyn and PyMC. Review data inputs assumptions transformations and validation steps to ensure reliable outcomes.
Marketing & Attribution Analytics: Guide multi-touch attribution incrementality testing spend optimization lead scoring market basket analysis and CLTV use cases.
Causal Inference & Experimentation: Lead A/B testing uplift modeling and statistical analysis. Ensure correct experiment design execution and interpretation.
Demand Forecasting & Optimization: Oversee demand forecasting considering seasonality trends and external factors. Support price checks and simple optimization analysis.
MLOps & Production Readiness: Oversee model deployment retraining workflows CI/CD pipelines and monitoring. Ensure models are production-ready and reliable.
Cloud & Data Engineering: Use GCP AWS or Azure to run scalable machine learning workloads. Review data pipelines storage and processing for efficiency and reliability.
Python Programming: Strong hands-on experience with Python including pandas NumPy and scikit-learn with basic exposure to TensorFlow or PyTorch.
SQL & Data Warehousing: Strong experience with SQL and data warehouses such as BigQuery Snowflake or Redshift for data extraction and analysis.
Business Communication: Translate technical work into clear business recommendations build ROI views and present insights to senior and non-technical stakeholders.
Process & Governance: Enforce standard workflows naming conventions documentation and data handling practices across projects.
Continuous Learning & Team Development: Stay updated on relevant ML MLOps and cloud tools. Support learning and growth of team members.
Marketing & Advertising Knowledge: Strong understanding of marketing and advertising KPIs and how data science outputs support decision-making.
Ranking & Recommendation Systems: Exposure to ranking or basic recommendation system use cases is a plus.

Who you are

Python Programming (46 years): Strong coding skills using pandas NumPy and scikit-learn with basic experience in TensorFlow or PyTorch.
Machine Learning & LLMs (46 years): Hands-on experience with core ML techniques simple deep learning models and applied LLM usage in business projects.
SQL & Data Warehousing (45 years): Experience working with BigQuery Snowflake or Redshift for data extraction joins and analysis.
MLOps & CI/CD (34 years): Experience with Docker Kubernetes basics MLflow Airflow and running and monitoring ML pipelines.
Marketing & Attribution Modeling (34 years): Strong base in MMM inputs causal checks attribution logic and model validation.
Marketing Mix Modelling: MMM (46 years): Hands-on experience with Meridian Robyn and PyMC-based MMM frameworks.
Marketing Analytics Domain (46 years): Experience working on use cases such as spend optimization lead scoring MTA market basket analysis CLTV analysis and incrementality lift testing.
Cloud Platforms (34 years): Experience running and managing machine learning workloads on GCP AWS or Azure.
Technical Leadership (23 years): Experience leading data science workstreams reviewing technical outputs and guiding solution design.
People Management & Delivery Ownership (23 years): Experience managing and mentoring 13 team members owning delivery timelines and scaling execution through a team