We are Brainlabs, the High-Performance media agency, on a mission to become the world's 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 company.

In 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! That's 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 :

- Work on end-to-end data science tasks from data prep to model creation.

- Track progress, manage day-to-day work, and support the team in meeting delivery timelines.

Machine Learning & Advanced Analytics :

- Develop ML models (regression, classification, clustering, NLP, deep learning, LLMs) for marketing, pricing, and customer insights.

MLOps & Engineering :

- Architect and maintain scalable ML infrastructure, CI/CD pipelines, and automated model retraining workflows.

- Ensure data quality, integrity, and efficiency by optimizing data storage, processing, and retrieval.

Marketing & Attribution Modeling :

- Design and implement Bayesian Marketing Mix Models (MMM) and multi-touch attribution solutions.

- Causal Inference & Experimental Design: Conduct A/B testing, uplift modeling, and statistical analysis to guide business decisions.

Demand Forecasting & Price Optimization :

- Support forecasting work involving seasonality, external factors, and simple price checks.

Cloud & Data Engineering Support :

- Leverage GCP, AWS, or Azure to deploy scalable machine learning pipelines.

- Design scalable, efficient, and secure data models, structures, and governance frameworks to support business needs.

Business Communication :

- Translate complex insights into actionable recommendations, develop ROI frameworks, and present to executives.

- Communicate complex technical concepts clearly to both technical and non-technical stakeholders, ensuring alignment across teams.

Team Collaboration & Mentorship :

- Assist junior Specialists with basic guidance and share working tips.

- Work with the DS team to support shared tasks.

Process Adherence :

- Follow standard methods, naming rules, and data handling steps.

- Support documentation and project tracking.

- Continuous Learning : Learn new ML, cloud, and MLOps tools as needed for project growth.

Who You Are :

- Python Programming : Strong coding skill with pandas, NumPy, scikit-learn, TensorFlow/PyTorch basics.

- Machine Learning & LLMs : Experience with core ML, simple deep learning, and basic LLM usage in projects.

- SQL & Data Warehousing : Work with BigQuery, Snowflake, or Redshift for data extraction and joins.

- MLOps & CI/CD : Exposure to Docker, Kubernetes basics, MLflow, Airflow, and simple pipeline runs.

- Marketing & Attribution Modeling : Good base in MMM inputs, causal checks, and attribution support.

- Market Mix Modelling MMM : Work on Meridian, Robyn, PyMC algorithms.

- Team Management : Manage and guide 1 to 2 team members.

- Marketing Analytics Domain : Work on marketing analytics based use cases such as Spend Optimization, Lead Scoring, MTA, Market Basket Analysis, CLTV Analysis, Incrementality Lift Testing etc.

- Cloud Platforms: Experience running workloads on GCP, AWS or Azure.

Qualification :

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

Good To Have Skills :

- Good understanding of advertising KPIs.

- Experience with ranking or basic recommendation work.