Associate Data Scientist

Position Summary

Systems Enginuity, Inc. (SEI) is seeking a Data Scientist / Analytics Engineer to support innovative FAA aviation safety research and the development of enterprise data and analytics capabilities. This early career position provides an opportunity to apply data science, statistical analysis, machine learning, and data engineering techniques to complex aviation safety and operational datasets.

Work collaboratively with aviation safety researchers, data scientists, and engineers to integrate, process, analyze, and visualize data related to aviation safety events, aircraft operations, system performance, weather, and National Airspace System safety.

You will develop analytical datasets, data processing pipelines, machine learning applications, and interactive visualizations within platforms such as Palantir Foundry and other enterprise data environments.

Working in a cross-functional team, you will help transform complex aviation data into meaningful safety indicators, analytical products, and actionable insights that support FAA safety analysis, risk assessment, and oversight that protects the flying public.

Key Responsibilities

• Perform exploratory data analysis, statistical analysis, data mining, and time-series analysis to identify trends, patterns, anomalies, and factors affecting aviation safety and operational performance.
• Develop and apply statistical, machine learning, and natural language processing (NLP) techniques to analyze structured and unstructured aviation data, including safety reports, operational events, aircraft performance, and related information.
• Support development and evaluation of analytical models for aviation safety event classification, contributing factor identification, anomaly detection, and safety performance monitoring.
• Develop and maintain Python- and SQL-based data processing workflows to extract, clean, transform, integrate, and prepare complex aviation datasets for analysis.
• Support development of reusable data transformations, analytical pipelines, and curated datasets within enterprise analytics environments, including Palantir Foundry or comparable platforms.
• Evaluate data quality, completeness, consistency, and relationships across multiple datasets, and implement validation checks and documentation to support reliable and reproducible analytical results.
• Develop safety indicators, analytical summaries, interactive dashboards, and visualizations to communicate operational trends, emerging safety concerns, and other actionable findings.
• Document analytical methods, data transformations, model assumptions, validation results, and findings to support reproducibility, technical reviews, and ongoing use of analytical products.

Required Qualifications

• Bachelor's or Master’s degree in Data Science, Computer Science, Mathematics, Engineering, Physics, or related quantitative or technical field.
• Academic research, internships, capstone projects, graduate research, or professional experience in data science, analytics, software development, or a related field:
• 1+ year of experience with Bachelor’s degree, or
• No prior professional experience required with Master’s degree.
• Strong foundation in Python and familiarity with SQL and relational data concepts.
• Experience with or academic exposure to data analysis and scientific computing libraries such as Pandas, NumPy, Scikit Learn, or comparable tools.
• Understanding statistical analysis, exploratory data analysis, data preparation, and basic machine learning concepts.
• Familiarity with processing techniques for structured and unstructured data.
• Ability to develop well-organized, documented, and reproducible analytical code.
• Strong analytical and problem-solving skills, with demonstrated ability to work both independently and collaboratively in a team.
• Strong written and verbal communication skills, including the ability to document analytical methods and clearly present findings to technical and non-technical audiences.

Preferred Qualifications

• Experience with Palantir Foundry, Databricks, Microsoft Azure data services, Snowflake, or comparable enterprise data and analytics platforms.
• Familiarity with enterprise data pipelines, ETL/ELT processes, data integration, data quality management, or analytical workflow development.
• Experience with natural language processing (NLP) techniques such as text classification, regular expressions, text embeddings, or other methods for analyzing unstructured data.
• Exposure to machine learning techniques such as clustering, classification, regression, anomaly detection, or time-series modeling.
• Experience developing dashboards or data visualizations.

Our Interview Process

At SEI, we believe the interview process should be personal, transparent, and authentic. We do not use AI to conduct interviews. Selected candidates will meet directly with SEI Project Engineers and Hiring Managers in live online interviews to discuss qualifications, experience, and potential fit within our team and culture.

To ensure a fair evaluation process, we ask candidates not to use AI tools or other assistance during interviews. We evaluate each candidate based on their own knowledge, skills, experience, and problem-solving abilities.

Eligibility Requirements

Candidates who receive and accept an offer of employment with SEI must successfully complete a U.S. Federal Government public trust security process, which includes fingerprinting, a government conducted background investigation, and other required screenings.

Due to the requirements of the FAA contract supporting this position, applicants MUST BE a U.S. citizen or lawful PERMANENT resident and eligible to satisfy applicable U.S. Federal Government suitability and security requirements. SEI is unable to provide employment visa sponsorship for this position.

Individuals working under or requiring temporary employment authorization, including F 1 CPT, OPT, or STEM OPT, are not eligible.

Pay: $67,000.00 - $82,000.00 per year

Benefits:

• 401(k)
• 401(k) matching
• Dental insurance
• Flexible schedule
• Health insurance
• Paid time off
• Parental leave
• Retirement plan
• Vision insurance

Work Location: Remote