[Hiring] Senior Data Scientist @Branch Metrics

About the Role

The SAAS team at Branch is responsible for developing and maintaining the core measurement and attribution platform that powers mobile marketing for thousands of leading apps worldwide. Our data science team tackles some of the most complex challenges in ad tech, including probabilistic attribution across billions of daily events, real-time fraud detection, and incrementality measurement. We work at the intersection of machine learning, distributed systems, and product development to deliver solutions that directly impact our customers' marketing ROI.

What You’ll Do

• Lead the design, development, and deployment of high-impact machine learning models
• Drive complex, ambiguous, and high-scale ML projects from initial research and proof-of-concept through to large-scale deployment, working closely with software engineering teams
• Design and execute end-to-end statistical modeling approach, measure model performance, and statistically analyze results to drive continuous product improvement
• Perform hands-on analysis and modeling of enormous, complex datasets to identify predictive signals and develop new features that enhance probabilistic attribution performance, fraud prevention, incrementality measurement, and anomaly detection
• Establish scalable, efficient, and automated processes for large-scale data analysis, machine learning model development, validation, and serving
• Stay abreast of the latest research in ML, deep learning, optimization, and Ad Tech
• Apply new, innovative approaches to Branch's unique challenges in mobile marketing measurement and attribution
• Communicate complex findings and product vision to engineers, product managers, and business stakeholders, influencing the company's roadmap

What you Bring

• 4+ years of professional experience building and deploying machine learning models for business applications.
• Computer Science, Engineering, Machine Learning, Statistics, or a related quantitative field, degree in a related field and 4+ years of relevant experience.
• Strong programming proficiency in one or more relevant languages (Python, SQL).
• Deep expertise in foundational computer science areas, including algorithms and data structures, numerical optimization, data mining, and distributed computing (e.g., Spark, presto).
• Experience with ML frameworks and libraries (Spark, pandas, Scikit-learn).
• Proven ability to translate business problems into mathematical and ML frameworks.
• Proven ability to conduct RND and Ad-hoc data analysis with excellent presentation skills. Good knowledge of Data visualization and BI tools (Superset, Looker, Tableau)
• Familiarity with AWS

Nice to Have

• Experience in professional software development practices, including system design, code review, and production environment management.
• Deep familiarity with the Ad Tech ecosystem (e.g., DSPs, SSPs, Exchanges, Advertiser/Publisher platforms) and related challenges like anti-fraud systems.
• Experience working with massive-scale data (billions of daily events) and petabyte-scale data processing systems.
• Prior experience developing models specifically for recommender systems, personalization, or large-scale optimization problems.

• • User level knowledge of Kubernetes and Bazel build tool.

This role does not qualify for relocation or visa sponsorship.

This role is 100% remote in Canada. This role is not eligible for remote work in any other location.

In accordance with applicable law, the following represents a reasonable estimated compensation range for this role: the estimated pay range for this role, if based in Canada is 148,000 CAD to 189,000 CAD. Please note that this information is provided for those hired in Canada only. Compensation for candidates outside of Canada will be based on the candidate’s specific work location. Actual compensation will be determined based on skills, experience, and geographic location and may be more or less than the amount shown above.