Forward Deployed Engineer (Data Science & ML)
On-Site, San Francisco
About BlueAlpha
BlueAlpha helps growth organizations make decisions with strategic confidence and execute with greater operational efficiency. Our econometrics and causal inference models reveal what drives revenue, while our agentic marketing infrastructure turns those insights into action by automating workflows across growth operations. We’re already working with large enterprises to bring these capabilities into their teams.
We bring together data engineering, applied machine learning, and AI agents to solve real customer problems in production. We challenge ideas, share openly, and strive for excellence without ego. If you want to shape how growth teams make decisions and build the systems that help them act, this is your chance.
Role Overview
As a Forward Deployed Engineer at BlueAlpha, you sit at the edge between our platform and our customers. You’ll embed with growth and marketing teams, map their problems, and turn them into concrete data science and engineering workstreams. You’ll prototype, ship, and iterate on solutions that combine:
Data science (incrementality tests, MMM-style models, causal inference, forecasting)
Data engineering (pipelines, modeling layers, data quality)
Software and ML engineering (APIs, jobs, model deployment, agent workflows)
You’re comfortable being hands-on in Python and SQL, sketching experiment designs, and jumping on a call with a VP of Growth to explain what the model is actually saying and what they should do on Monday.
This is a high-ownership role: you’ll directly shape how we deliver value to customers and what gets built into the core product.
Responsibilities
Own technical delivery for customer deployments from first prototype to production.
Build and maintain data pipelines (Python + SQL) that integrate marketing, product, and revenue data.
Develop and iterate on analytical and ML workflows (experiments, causal analysis, forecasting, response curves).
Turn analyses into reliable jobs or small services, not one-off notebooks.
Work directly with customers to understand problems, translate them into clear technical work, and present results and recommendations.
Design and evaluate experiments (geo holdouts, incrementality tests) with clear metrics and interpretation.
Generalize common patterns into reusable tools, templates, or product features.
Collaborate with core engineering on APIs, data models, and backend components needed for smoother deployments.
Qualifications
Required
4+ years in data science, analytics, data engineering, ML engineering, forward deployed engineering, or consulting roles, ideally with some client-facing component.
Strong Python and SQL skills; you’re comfortable owning analyses, pipelines, and small services end-to-end.
Solid grounding in statistics and experimentation (e.g., holdouts, causal inference basics, regression, time series).
Experience working with real-world business data (product, marketing, revenue, or similar) where things are messy and ambiguous.
Ability to move between exploration and production: from notebook to pipeline to deployed job or service.
Strong communication: you can walk a VP of Growth through a model’s recommendations and also review a PR with an engineer.
Comfort in a fast-paced startup: limited structure, high autonomy, and lots of context-switching.
Nice to Have
Experience with marketing or growth analytics, MMM, incrementality testing, or attribution.
Familiarity with modern data stacks: Snowflake, BigQuery, Redshift, Fivetran, Stitch, etc.
Experience deploying ML models or analytical workloads to production (batch or real-time).
Background in management consulting, strategy, or client services with strong quantitative work.
Comfort with light software engineering: building APIs, small internal tools, or integrating with external APIs.
Compensation & Benefits
Compensation: Base salary of $100,000–$180,000 per year, depending on experience, plus meaningful equity.
Benefits: Health insurance, flexible PTO, and remote-friendly work.
Impact: Work on multifaceted problems end-to-end.
Culture: A collaborative, high-energy environment where we challenge ideas, not people. Small team, big ambition.
How to Apply
Ready to help define the future of AI-driven marketing? Send your resume and a short note to careers@bluealpha.ai.
