Senior Data Scientist

This is a fully remote position, open to applicants in Colorado, +3 more states.

📋 Description

• Oversee the design, development, deployment, and enhancement of machine learning, predictive analytics, and AI-driven solutions.

• Convert business challenges and opportunities into analytical strategies, model specifications, and measurable success benchmarks.

• Utilize advanced statistical analysis, machine learning methods, and data science techniques to address intricate business issues.

• Examine extensive, complex datasets to uncover trends, patterns, opportunities, and actionable insights.

• Create and sustain model documentation, technical specifications, and implementation strategies.

• Keep abreast of emerging technologies, tools, and best practices in data science, machine learning, and artificial intelligence.

• Design and implement thorough validation and evaluation strategies for machine learning and generative AI solutions.

• Establish benchmarking frameworks and success metrics to evaluate model performance, reliability, and business impact.

• Assess model quality using both quantitative and qualitative metrics, including accuracy, precision, recall, robustness, latency, and business outcome indicators.

• Evaluate generative AI applications for response quality, grounding, relevance, consistency, and hallucination risk.

• Identify and address risks associated with bias, fairness, explainability, privacy, and model dependability.

• Conduct model validation, testing, and performance evaluations before production deployment.

• Set up monitoring processes and evaluation methodologies to ensure ongoing model effectiveness and alignment with business goals.

• Design, execute, and analyze experiments, including A/B tests and statistical studies, to assess product and business outcomes.

• Define key performance indicators and success metrics for machine learning and AI projects.

• Measure and convey the impact of analytical solutions through statistical analysis and quantitative techniques.

• Collaborate with stakeholders to establish hypotheses, success criteria, and decision-making frameworks.

• Leverage experimentation and data-driven insights to inform product, operational, and strategic choices.

• Work alongside Engineering and Data Engineering teams to implement, operationalize, and scale models within production settings.

• Monitor deployed models for performance decline, model drift, data quality issues, and shifting business circumstances.

• Suggest retraining, optimization, or replacement strategies based on model performance and changing business needs.

• Assist in the development of scalable, maintainable, and dependable AI and machine learning solutions.

• Ensure model deployment processes adhere to engineering best practices and operational requirements.

• Collaborate with Product, Engineering, Analytics, and business stakeholders to prioritize opportunities and deliver impactful solutions.

• Explain complex analytical results and technical concepts to both technical and non-technical audiences.

• Present recommendations, insights, and model performance outcomes to leadership and project teams.

• Aid in technical reviews, project planning, and delivery activities across cross-functional initiatives.

• Contribute to knowledge sharing, documentation, and best practices within the data science team.

• Provide technical guidance and mentorship to junior team members and peers as necessary.

⛳️ Requirements

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative discipline; Master's degree preferred.

• Over 7 years of experience in data science, machine learning, advanced analytics, or a related field.

• Proven experience in developing and deploying machine learning models in production settings.

• Solid foundation in statistics, hypothesis testing, experimental design, and predictive modeling.

• Experience handling large datasets and working in distributed data processing environments.

• Proficiency in Python, SQL, and prevalent data science and machine learning frameworks.

• Experience in conveying analytical findings and recommendations to both business and technical stakeholders.

• Demonstrated capability to lead projects and collaborate effectively across cross-functional teams.

🏝️ Benefits

• Stock options

• A variety of medical benefits

• Dental benefits

• Vision benefits

• Financial benefits

• Generous paid time off (PTO)

• Stipends for professional development

• Wellness benefits