USD per year
Job Title
Senior Forward Deployed Data Scientist/Engineer
Location
San Francisco, CA; New York, NY
Remote Work Allowance
No explicit mention of remote work allowance is provided.
Employment Type
Full-time (explicitly mentioned in salary section)
Experience Level
Senior (implied by job title and 5+ years experience requirement)
Job Description
Join the team shaping the future of AI at Scale. At Scale AI, we help leading enterprises turn AI from a promising capability into reliable systems that improve real workflows and deliver measurable business value. We are hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment. This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production. In many cases, the data scientist builds the first usable version of the solution, proves value quickly, and helps drive it into a durable product or platform capability. The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.
What you’ll do
- Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria
- Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans
- Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems
- Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration
- Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations
- Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement
- Use AI-assisted development workflows to accelerate prototyping and product iteration while maintaining strong engineering discipline
- Diagnose failure modes across data quality, model behavior retrieval workflow design user experience; drive fixes into production
- Act as the voice of the customer to Product Engineering Data Science teams using field learnings to shape roadmap platform capabilities
What we’re looking for
- 5+ years of experience in data science machine learning quantitative engineering or another highly analytical technical role
- Proven track record of shipping data ML AI systems delivering measurable business or product impact
- Exceptional ability to structure ambiguous problems define success metrics translate them into executable technical plans
- Strong foundation in statistics experimentation causal reasoning measurement
- Experience building tools products (not just analyses) such as internal workflow tools evaluation systems operator-facing products experimentation platforms customer-specific applications
- Hands-on fluency in Python SQL modern data AI tooling able to inspect data prototype quickly debug deeply productionize solutions that work
- Comfort using AI-assisted coding development workflows for rapid idea-to-product iteration
- Strong communication stakeholder management skills working effectively with customers engineers product teams executives
- High ownership bias toward shipping in fast-moving environments with incomplete information
Preferred qualifications
- Experience in forward deployed solutions consulting client-facing technical roles
- Experience designing evaluation frameworks for LLMs retrieval systems agentic workflows AI-enabled products
- Experience with large-scale data processing distributed systems such as Spark Ray Airflow
- Experience with cloud infrastructure modern data platforms such as AWS GCP Snowflake BigQuery
- Experience building lightweight applications APIs internal tools workflow software on top of data ML systems
- Familiarity with marketplace experimentation causal inference forecasting optimization advanced statistical modeling
- Strong product instinct judgment knowing when solution is model experiment tool workflow redesign
What success looks like
Success means taking messy high-stakes customer problems into deployed systems actually used—models evaluation frameworks operator-facing tools lightweight data products—that change decision-making. Success defined by measurable impact rugged evaluation reliable execution.
Compensation & Benefits
Compensation packages include base salary + equity + benefits. Salary range for full-time position in San Francisco New York Seattle: $167200—$209000 USD Benefits include comprehensive health dental vision coverage retirement benefits learning development stipend generous PTO May be eligible for commuter stipend.
Skills Mentioned
Programming Languages:
- Python
- SQL
Tools & Platforms:
- Modern data AI tooling
- Spark
- Ray
- Airflow
- AWS
- GCP
- Snowflake
- BigQuery
Methodologies & Concepts:
- Statistical modeling
- Experimentation design
- Causal inference
- Metric design
- Forecasting
- Segmentation
- Diagnostics
- Performance measurement
- Evaluation frameworks for ML / LLMs / retrieval systems / agentic workflows / AI-enabled products
- Marketplace experimentation
- Optimization
Soft Skills:
- First-principles problem solving
- Rigorous measurement & technical execution
- Communication & stakeholder management skills (customers product teams executives)
- High ownership & bias toward shipping under uncertainty
Other: AI-assisted coding development workflows
Scale AI provides high-quality data and full-stack technologies that power the world’s leading models and enable enterprises and governments to build, deploy, and oversee AI applications that deliver real impact. They offer a data-centric, end-to-end solution to manage the entire machine learning lifecycle, combining cutting edge technology with operational excellence to help teams develop the highest-quality datasets.
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