Data Scientist; Remote

Position: 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.

Minimum Requirements
- 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.

Job Specific Requirements:

-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…