Manager, AI and Data Science

This is a fully remote position, open to applicants in Alaska, +26 more states.

📋 Description

• Assemble and lead a high-achieving team of data scientists, machine learning specialists, and experimental engineers.

• Foster alignment between advances in AI and the overarching objectives of the organization.

• Facilitate collaboration across various departments, including business, analytics, and technical teams.

• Investigate, create, and iteratively test advanced AI/ML models for strategic insights and business solutions.

• Advocate for experimentation, rapid prototyping, and validation driven by data.

• Supervise the monitoring of model performance, drift detection, retraining strategies, and issue resolution.

• Assess the strategic impact and business value of AI/ML prototypes and production-ready models.

• Promote peer review, reproducible experimentation, and responsible AI principles such as fairness and explainability.

• Guide and mentor data scientists, machine learning scientists, and experimental engineers.

• Establish agile-like practices for experimentation, documentation, retrospectives, and process enhancements.

• Maintain thorough documentation for experimental design, model development, and data usage to ensure compliance and reproducibility.

• Collaborate with business leaders to translate complex scientific concepts into clear narratives for data-driven decision-making.

⛳️ Requirements

• Bachelor’s Degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline; or 5+ years of relevant professional experience.

• 2+ years of experience in leading analytical and scientific teams focused on data science or machine learning.

• 5+ years of practical experience in developing and validating AI/ML solutions and transitioning models from research to pilot or proof of concept.

• 5+ years of experience in conducting quantitative analytics.

• Preferred: advanced degree (Masters/PhD) in a quantitative, computational, or scientific field.

• Preferred: 2+ years managing cross-functional research collaborations or partnerships between academia and industry focused on AI/ML development.

• Preferred: 5+ years of experience with NumPy, Pandas, Matplotlib, scikit-learn, SHAP, LIME, Statsmodels, and PyMC3.

• Preferred: experience with Hugging Face Transformers, SpaCy, XGBoost, or LightGBM.

• Preferred: 5+ years of productionizing and monitoring AI models using MLOps frameworks such as MLflow or Kubeflow.

• Preferred: 5+ years working in Agile-like test-and-learn environments.

• Preferred: 5+ years of experience in healthcare and healthcare data.

• Preferred: 2+ years of implementing responsible AI practices.

• Experience with deep learning architectures and frameworks such as TensorFlow, PyTorch, and Keras.

• Proficient in debugging ML/AI models and enhancing their predictive capabilities.

• Experience with hypothesis-driven development, rapid prototyping, and iterative model refinement.

• Experience applying product development lifecycle methodologies to data-centric products.

• Familiarity with software design patterns, microservices, distributed computing, and container orchestration.

• Proficient in SQL for data exploration and feature engineering.

• Experience with statistical analyses including hypothesis testing, experimental design, regression, clustering, time series analysis, anomaly detection, and sequence analysis.

• Experience in developing supervised predictive models and utilizing unsupervised learning techniques.

• Comprehensive knowledge of modern deep learning models and architectures.

• Practical expertise in generative AI, prompt engineering, reasoning strategies, agentic frameworks, function calling, and retrieval-augmented generation patterns.

• Demonstrated proficiency in leading large-scale prompt engineering projects.

• Strong communication, collaboration, mentorship, and team leadership abilities.

• Capability to meet the sedentary physical requirements, operate a keyboard, and communicate effectively.

🏝️ Benefits

• Medical, vision, and dental insurance with low employee premiums.

• Optional benefit offerings, including pet insurance.

• Life and disability insurance coverage.

• Retirement plans, including a 401K employer match and a pension plan vested after 3 years of service.

• Wellness incentives, including counseling services, stress management programs, and mindfulness initiatives.

• Generous paid time off policy.

• Tuition assistance for both undergraduate and graduate studies.

• Employee recognition program to celebrate achievements.

• Commuter benefits to ease travel expenses.

• Free convenient on-site parking.

• Subsidized on-campus cafes for meals.

• On-site health and wellness events, coffee connects, disaster preparedness fairs, and various activities.

• Fitness and well-being center offering in-person and virtual workouts along with nutritional counseling.