Staff Data Scientist

robotsandpencils; United States; Remote; USD 140,000 - 230,000; Full time

Job summary

Robots and Pencils seeks a senior data scientist to lead applied data science work on complex ML and AI problems from framing questions to validating and deploying solutions.

You will set scientific direction on client engagements, collaborate across product and engineering teams, and clearly explain results to technical and business audiences.

Qualifications

• A PhD, or a master’s degree with at least four years of quantitative experience.
• 5+ years in data science, statistics, or applied ML, including 3+ years building business models.
• Strong Python or R skills with libraries such as scikit-learn and TensorFlow or PyTorch.

Responsibilities

• Design and evaluate predictive or prescriptive models for customer behavior and performance.
• Lead ML and generative AI projects from proof of concept through production deployment.
• Establish scalable data analysis, model development, validation, and serving processes.
• Run controlled experiments and causal inference to test hypotheses and measure outcomes.
• Translate complex data findings into actionable recommendations with clear visuals.
• Guide cross-functional teams, mentor data scientists, and create reusable tools.

Skills

Python

R

scikit-learn

TensorFlow

PyTorch

Java

C++

Data analysis

Experiment design

Education

PhD

Master's degree (Quantitative field)

Tools

Databricks

AWS SageMaker

Snowflake

ML frameworks

Job description

Role overview

Lead applied data science work on complex machine learning and AI problems, from framing an ambiguous business question to validating and deploying a solution. You will set scientific direction on client engagements, collaborate across product and engineering teams, and explain results clearly to technical and business audiences.

Responsibilities

• Design and evaluate predictive or prescriptive models for challenges such as customer behavior, operational performance, and personalization.
• Lead machine learning and generative AI projects from proof of concept through production, including model optimization and deployment.
• Establish scalable processes for data analysis, model development, validation, and serving.
• Use controlled experiments, multivariate testing, and causal inference to test hypotheses and measure outcomes.
• Analyze complex datasets and turn findings into recommendations, communicating methods and results with clear visualizations.
• Guide technical work across teams, mentor data scientists, research useful approaches, and create reusable tools and processes.

Requirements

• At least five years of professional data science, statistics, or applied machine learning experience, including three or more years building business models.
• A PhD, or a master’s degree with at least four years of experience, in a quantitative field such as computer science, statistics, mathematics, engineering, or machine learning.
• Strong Python or R skills and experience with libraries such as scikit-learn and TensorFlow or PyTorch; familiarity with algorithms and ontologies.
• Programming experience in Java, C++, or a related language.
• Applied modeling experience in areas such as statistical methods, forecasting, NLP, or optimization.
• Experience designing experiments, deploying models through APIs, pipelines, or ML frameworks, and working with Databricks, AWS SageMaker, and Snowflake.
• Experience building and deploying Data Mesh architectures.

Nice to have

• Palantir experience or AWS cloud and machine learning certifications.

Benefits and work setup

• Work across client engagements with scientists, data engineers, developers, and product partners.
• The role offers autonomy over technical direction and includes mentoring and cross-team leadership.