Data Scientist; Remote

Essential Duties and Responsibilities

• Perform hands-on data analysis and modeling with huge data sets.
• Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms.
• Work side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products.
• Discover data sources, get access to them, import them, clean them up, and make them "model-ready.".
• Create and refine features from the underlying data.
• Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your optimizations and communicate results to peers and leaders.
• Explore new design or technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
• Collect, validate, clean, integrate, and analyze data from multiple sources, including the Human Performance Data Management System (HPDMS).
• Conduct exploratory, statistical, and predictive analyses to identify trends, correlations, risks, and opportunities related to human performance and mission readiness.
• Develop and maintain databases, spreadsheets, reports, and automated dashboards that communicate program performance and outcomes.
• Support survey design, administration, analysis, and interpretation to inform program improvements.
• Collaborate with program staff, biostatisticians, clinicians, and other cross-functional partners to translate findings into actionable recommendations.
• Develop, document, and refine analytical methods, models, and tools that address complex operational and health-related challenges.
• Present analytical findings clearly to technical and nontechnical stakeholders while protecting sensitive information.
• Perform other duties as assigned.

• Bachelor's degree in relevant field of study and 3+ years of relevant professional experience required, or equivalent combination of education and experience.
• Advanced degree in Computer Science, Information Systems, Business Analytics, Mathematics, Statistics, Engineering, Business Administration or a related field preferred.
• 1-3+ years of professional experience with applying quantitative research in optimizing human decisions using technologies like machine learning and/or deep learning.
• 1+ years using major machine learning/deep learning frameworks (e.g., Scikit-learn, PyTorch, Tensor Flow and Keras) and algorithms (e.g., CNN, GAN, LSTM, RNN, XGBOOST).
• 1+ years of data engineering experience with modern big data analytics architectures (Hadoop, SQL, HIVE, Spark, Snowflake, etc.) on major cloud platforms (e.g., AWS, Azure, Google Cloud).
• 1+ years programming skill in Python, Scala, or Julia.
• Working knowledge with modern cloud-based data storage and compute environments (e.g., AWS Sagemaker, Databricks in Azure, AI-platform in GCP, etc.).
• Experience deploying ML models into discovery/production environment to drive insights using MLOps a plus.
• Experience working in an agile delivery model a plus.
• Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques.
• Ability to communicate complex ideas in a clear, precise, and actionable manner.
• Excellent communication and presentation skills, with the ability to articulate new ideas and concepts to technical and non-technical partners.
• PowerBI experience a plus.

• Bachelor's degree in data science, statistics, mathematics, computer science, or a related field.
• Demonstrated experience using statistical analysis tools, database systems, and data visualization platforms.
• Experience preparing, analyzing, and interpreting complex datasets.
• Ability to communicate technical findings to diverse audiences.
• Security:
  Requires anactive Secret security clearance and U.S. citizenship.
• Survey Design & Analysis:
  Assist in designing surveys, collecting, and analyzing survey data to inform program improvements
  
  Collaboration:
  
  Work with cross-functional teams, including biostatisticians, to develop data-driven recommendations for SOF and family support initiatives.
• Technical Solutions:
  Develop and refine analytical methods and tools to address complex operational and health-related challenges.
• Experience supporting government, defense, military health, or human performance programs.
• Experience developing automated dashboards, predictive models, or decision-support tools.
• Knowledge of data governance, privacy, security, and quality-control practices.
• Familiarity with multidisciplinary…