> Markdown version of [/jobs/ext/2211045-senior-data-scientist-algorithm-lyft-biz](https://www.wearedevelopers.com/jobs/ext/2211045-senior-data-scientist-algorithm-lyft-biz). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist, Algorithm, Lyft Biz - **Company:** Lyft Inc - **Location:** Seattle, WA, United States (Remote available) - **Experience:** Expert - **Salary:** $136,160.0 - $170,200.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Algorithm Design, Data Analysis, Program Optimization, Distributed Data Store, Python (Programming Language), Machine Learning, Tensorflow, Software Deployment, Reinforcement Learning, Feature Engineering, Pytorch, Snowflake, Apache Spark, Scikit Learn, Information Technology, Machine Learning Operations, Unsupervised Learning, Databricks - **Published:** August 24, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pelepham03 ## About the Role This is a high-visibility, high-impact role with direct influence on Lyft's enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of technical leadership in fast-paced, cross-functional environments., * Master's or PhD in Machine Learning, Computer Science, Statistics, Optimization, or a related quantitative field (or equivalent applied experience) * Industry Background: 5+ years of hands-on experience developing, deploying, and maintaining production machine learning models and optimization systems. * Core Technical Expertise: Deep knowledge of supervised/unsupervised learning, ranking/decisioning systems, probabilistic modeling, and causal inference. * Technical Stack: Strong proficiency in Python, modern ML frameworks (PyTorch, TensorFlow, scikit-learn), and distributed data systems (Spark, Snowflake, Databricks). * Production ML Systems: Hands-on experience building end-to-end ML architectures, including online/batch pipelines, feature engineering, and automated monitoring frameworks. * Experimental Design: Demonstrated track record of designing rigorous experimentation strategies, A/B tests, and offline/online validation methodologies. * Domain Ownership: Proven ability to independently drive multi-project algorithmic scopes and navigate technical ambiguity from ideation to delivery.Communication & Leadership: Exceptional ability to translate complex technical concepts for non-technical stakeholders, alongside a history of mentoring peers and raising technical bars. ## Description * Technical Leadership: Lead complex Machine Learning, AI, and causal inference initiatives across Lyft Business products (Business Travel, Lyft Pass, Concierge) in ambiguous, high-impact problem spaces. * End-to-End Modelling: Own the complete lifecycle of algorithmic solutions-from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration. * Production Deployment: Partner closely with Engineering to build and scale production-grade ML systems, real-time inference services, batch pipelines, and feature stores. * Experimentation & Rigor: Define offline/online metrics, evaluation frameworks, and A/B testing strategies to ensure algorithms are reliable, fair, and aligned with business outcomes. * System Optimization: Continually improve model performance across latency, accuracy, cost, and reliability using advanced tuning and scientific rigor. * Algorithmic Innovation: Drive scientific excellence by introducing modern techniques in ML, optimization, reinforcement learning, or graph-based methods to unlock new product capabilities. * Cross-Functional Influence: Translate complex business challenges into concrete algorithmic solutions in close collaboration with Product, Engineering, Operations, and Science teams. * Mentorship & Quality Bar: Mentor junior and mid-level scientists, providing technical guidance, conducting modeling critiques, and contributing to Lyft's broader ML standards and tooling. ## Related Videos - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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