Data Scientist

Company Description

Mountain Cat LLC is a multidisciplinary team specializing in foreign language processing, data science, cloud computing, and application development in support of national defense and intelligence agency missions. The company brings together experts from diverse technical backgrounds to solve complex, mission-critical problems. Team members collaborate closely with government partners to design secure, scalable, and high-performance solutions. Mountain Cat offers a technically challenging environment where innovation, analytical rigor, and operational impact are highly valued.

• Engage with customers to determine the nature of requirement/analytic problem, evaluate options, and offer Information Technology (IT)-based recommendations/options
• Advise customers on IT methods and data needed and/or available to satisfy the requirement
• Develop IT solutions to enable the exploitation of databases and files; devise creative data collection and strategies
• Develop comprehensive software applications
• Identify potential additional data sources and automate collection processes
• Integrate, analyze, evaluate, and assess quantitative data (using statistical software, computer models, geospatial models, software languages, mathematical models, machine learning) to contribute to or develop IT solutions to requirements (software tools, analytic models, or reports.)
• Conduct statistical, mathematical, geospatial modeling or data-mining analysis in partnership with other colleagues
• Anticipate and project a wide range of possible outcomes using scenario/alternative analyses, machine learning, and agent based modeling or other advanced analytic techniques
• Identify, use, and/or develop a wide range of methodologies and analytic tools to address existing or potential problems and collection strategies
• Prepare, and communicate a wide range of strategic, highly complex graphics, computational models/tools, or written/oral assessments
• Leverage multiple data management tools to organize relevant information and make decisions

• Active TS/SCI clearance with Poly.
• Demonstrated experience building production data pipelines and ETL/ELT workflows at scale.
• Demonstrated experience with Apache Spark and PySpark for distributed data processing.
• Demonstrated experience with advanced Python programming skills including data manipulation libraries (Pandas, Num Py) and data engineering best practices.
• Demonstrated experience understanding data security, privacy, governance, and compliance principles.
• Demonstrated experience with workflow orchestration tools such as Step Functions and Airflow.
• Demonstrated experience with containerization such as Docker or Podman, and deploying data applications in cloud environments.
• Demonstrated experience with AWS services (in particular S3, Lambda, and Step Functions).
• Demonstrated experience with Postgre
  
  SQL and MySQL in production environments, including performance tuning and schema design.
• Demonstrated experience with SQL and query optimization for complex analytical workloads.
• Demonstrated experience with version control (Git) and CI/CD practices for data pipelines.
• Demonstrated experience working with stakeholders to understand data requirements, assess feasibility, and design appropriate solutions with minimal oversight.
• Demonstrated experience with strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks.