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 what’s 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. It’s 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. You’ve 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 it’s 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 (4–6 years): Strong coding skills using pandas, NumPy, and scikit-learn, with basic experience in TensorFlow or PyTorch.
- Machine Learning & LLMs (4–6 years): Hands-on experience with core ML techniques, simple deep learning models, and applied LLM usage in business projects.
- SQL & Data Warehousing (4–5 years): Experience working with BigQuery, Snowflake, or Redshift for data extraction, joins, and analysis.
- MLOps & CI/CD (3–4 years): Experience with Docker, Kubernetes basics, MLflow, Airflow, and running and monitoring ML pipelines.
- Marketing & Attribution Modeling (3–4 years): Strong base in MMM inputs, causal checks, attribution logic, and model validation.
- Marketing Mix Modelling: MMM (4–6 years): Hands-on experience with Meridian, Robyn, and PyMC-based MMM frameworks.
- Marketing Analytics Domain (4–6 years): Experience working on use cases such as spend optimization, lead scoring, MTA, market basket analysis, CLTV analysis, and incrementality lift testing.
- Cloud Platforms (3–4 years): Experience running and managing machine learning workloads on GCP, AWS, or Azure.
- Technical Leadership (2–3 years): Experience leading data science workstreams, reviewing technical outputs, and guiding solution design.
- People Management & Delivery Ownership (2–3 years): Experience managing and mentoring 1–3 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
Bachelor’s or Master’s 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?
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. 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.