Data Scientist

Summary

Prove is a digital identity company providing phone-centric identity tokenization and passive cryptographic authentication solutions for businesses. The Senior Data Scientist will develop and validate statistical and machine learning models, collaborate with machine learning engineers on production deployment and monitoring, and translate model performance into business and product recommendations.

Responsibilities

• Develop, validate, and tune statistical and machine learning models that solve complex business problems
• Partner with engineers to ensure models are designed with production deployment in mind
• Design experiments and evaluate models using robust statistical methodologies
• Build and maintain dashboards that proactively monitor product efficacy and distribute key insights across product and customer domains
• Collaborate with ML engineers on deployment pipelines, APIs, and infrastructure
• Proactively monitor deployed models for drift, accuracy, and reliability
• Provide insights and business recommendations based on model performance in production
• Recommend retraining or refinement strategies in response to performance changes
• Translate model results into actionable recommendations for both product and business teams
• Identify opportunities for model improvements that drive up-sell, revenue growth, and cost reduction
• Communicate results clearly to both technical and non-technical stakeholders
• Work side-by-side with Senior Machine Learning Engineers to ensure smooth handoff from research to deployment
• Mentor team in best practices for applied ML and production readiness
• Contribute to evolving data science standards and playbooks that prioritize operational impact

Skills

• This role is not eligible for work authorization sponsorship
• 5+ years of experience applying machine learning and statistics to business problems
• Master's or PhD in Statistics, Computer Science, Data Science, or related field (or equivalent experience)
• Prior exposure to production ML environments and workflows
• Strong proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow)
• Strong background in statistical methods (supervised/unsupervised learning, classification models, etc.), experimental design, and data visualization (Looker) and storytelling
• Strong proficiency in SQL (Snowflake) with an ability to work with raw data and collaborate with data engineering teams to optimize data pipelines
• Proficiency with cloud platforms (AWS)
• Solid understanding of APIs, model deployment processes, and monitoring practices
• Familiarity with other programming languages such as R, Java, and Go
• Excellent communication skills with ability to bridge technical and business contexts
• Strong problem-solving and proactive ownership mindset
• Comfort working in cross-functional teams with engineers, product managers, and business leaders
• Ability to balance quick iterations with building long-term scalable solutions

Qualifications

Must Haves

• This role is not eligible for work authorization sponsorship
• 5+ years of experience applying machine learning and statistics to business problems
• Master's or PhD in Statistics, Computer Science, Data Science, or related field (or equivalent experience)
• Prior exposure to production ML environments and workflows
• Strong proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow)
• Strong background in statistical methods (supervised/unsupervised learning, classification models, etc.), experimental design, and data visualization (Looker) and storytelling
• Strong proficiency in SQL (Snowflake) with an ability to work with raw data and collaborate with data engineering teams to optimize data pipelines
• Proficiency with cloud platforms (AWS)
• Solid understanding of APIs, model deployment processes, and monitoring practices
• Familiarity with other programming languages such as R, Java, and Go
• Excellent communication skills with ability to bridge technical and business contexts
• Strong problem-solving and proactive ownership mindset
• Comfort working in cross-functional teams with engineers, product managers, and business leaders
• Ability to balance quick iterations with building long-term scalable solutions

Benefits

• Bonus Plan (for eligible roles)
• Equity Plan
• Modern Health for financial, mental, and physical wellness
• 401(k) Retirement Plan & Match (US Offices)
• Unlimited Vacation and Flexible hours
• Comprehensive medical benefits for you and your family
• Emotional & Physical Wellness – Access to wellness services (EAP & Prove Well-Being Reimbursement)
• Bottomless snacks & beverages for certain office locations
• Daily GrubHub stipend for lunch if coming into the office (US Offices)