Branch Metrics
At Branch, we’re transforming how brands and users interact across digital platforms. Our mobile marketing and deep linking solutions are trusted to deliver seamless experiences that increase ROI, decrease wasted spend, and eliminate siloed attribution. Our Branch team consists of smart, humble, and collaborative people who value ownership over all. Everything we do is centered around creating a great product, team, and company that lives and breathes our motto: Build Together, Grow Together, Win Together.
We're seeking a Senior Data Scientist to provide strategic insights using advanced analytics, predictive modeling, and data-driven solutions. This role requires strong technical skills beyond traditional data science, including delivering production-ready code and collaborating closely with engineering teams. Domain experience in Ad Tech, fraud detection, anomaly detection, or causal AI are highly desirable.
As a Senior Data Scientist, you’ll get to:
Collaborate with stakeholders to identify data-driven business opportunities. Perform data mining, analytics, and predictive modeling to optimize business outcomes. Conduct extensive research and evaluate innovative approaches for new product initiatives. Develop, deploy, and monitor custom models and algorithms. Deliver end-to-end production-ready solutions through close collaboration with engineering and product teams. Identify opportunities to measure and monitor key performance metrics, assessing the effectiveness of existing ML-based products. Serve as a cross-functional advisor, proposing innovative solutions and guiding product and engineering teams toward the best approaches. Anticipate and clearly articulate potential risks in ML-driven products. Effectively integrate solutions into existing engineering infrastructure. You’ll be a good fit if you have:
4+ years of relevant experience in data science, analytics, or related fields. Degree in Statistics, Mathematics, Computer Science, or related field. Proficiency with Python, SQL, Spark, Bazel, CLI (Bash/Zsh). Expertise in Spark, Presto, Airflow, Docker, Kafka, Jupyter. Strong knowledge of ML frameworks (scikit-learn, pandas, xgboost, lightgbm). Experience deploying models to production on AWS infrastructure and experience with the basic AWS services. Advanced statistical knowledge (regression, A/B testing, Multi-Armed Bandits, time-series anomaly detection). Proven ability to deliver reproducible, production-quality code. Nice to Have:
Domain expertise in Ad Tech, Fraud Detection, Anomaly Detection, or Causal AI (strongly preferred). Startup experience and ability to work in a fast pace self-starter environment (strongly preferred). Experience with implementing GenAI driven applications, Agentic Applications, RAG, prompt engineering. Experience with technologies like Lang Chain, Lang Graph, LamaIndex etc. For this role, we're looking for candidates in the Denver metropolitan area for a remote position. We plan to grow our team and presence in Denver over time. This role does not qualify for relocation or visa sponsorship. Applications for this position will be open until Monday, June 2nd. 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 Colorado is $148,000 - $189,000. Please note that this information is provided for those hired in Colorado only. Compensation for candidates outside of Colorado 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.
#J-18808-Ljbffr
Collaborate with stakeholders to identify data-driven business opportunities. Perform data mining, analytics, and predictive modeling to optimize business outcomes. Conduct extensive research and evaluate innovative approaches for new product initiatives. Develop, deploy, and monitor custom models and algorithms. Deliver end-to-end production-ready solutions through close collaboration with engineering and product teams. Identify opportunities to measure and monitor key performance metrics, assessing the effectiveness of existing ML-based products. Serve as a cross-functional advisor, proposing innovative solutions and guiding product and engineering teams toward the best approaches. Anticipate and clearly articulate potential risks in ML-driven products. Effectively integrate solutions into existing engineering infrastructure. You’ll be a good fit if you have:
4+ years of relevant experience in data science, analytics, or related fields. Degree in Statistics, Mathematics, Computer Science, or related field. Proficiency with Python, SQL, Spark, Bazel, CLI (Bash/Zsh). Expertise in Spark, Presto, Airflow, Docker, Kafka, Jupyter. Strong knowledge of ML frameworks (scikit-learn, pandas, xgboost, lightgbm). Experience deploying models to production on AWS infrastructure and experience with the basic AWS services. Advanced statistical knowledge (regression, A/B testing, Multi-Armed Bandits, time-series anomaly detection). Proven ability to deliver reproducible, production-quality code. Nice to Have:
Domain expertise in Ad Tech, Fraud Detection, Anomaly Detection, or Causal AI (strongly preferred). Startup experience and ability to work in a fast pace self-starter environment (strongly preferred). Experience with implementing GenAI driven applications, Agentic Applications, RAG, prompt engineering. Experience with technologies like Lang Chain, Lang Graph, LamaIndex etc. For this role, we're looking for candidates in the Denver metropolitan area for a remote position. We plan to grow our team and presence in Denver over time. This role does not qualify for relocation or visa sponsorship. Applications for this position will be open until Monday, June 2nd. 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 Colorado is $148,000 - $189,000. Please note that this information is provided for those hired in Colorado only. Compensation for candidates outside of Colorado 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.
#J-18808-Ljbffr