Data Scientist

Position Overview

SteerBridge is seeking a Mid-Data Scientist to analyze multidimensional aviation, global supply chain, and operational data to develop and maintain predictive models. The ideal candidate has hands-on experience with statistical modeling, machine learning, and time-series analysis and is comfortable working with complex data from multiple sources and formats. Candidates must have hands-on experience with supervised learning, including classification and regression, and unsupervised learning, including clustering and dimensionality reduction. This role requires a quick learner who is curious, innovative, results-oriented, and able to identify meaningful trends and patterns within large, complex datasets. Strong interpersonal skills and the ability to work effectively with partners are also essential.

Key Responsibilities

• Develop, evaluate, and maintain predictive and statistical models.
• Lead or support end-to-end analytical modeling and data science framing activities.
• Analyze and integrate large, complex datasets from multiple sources and formats.
• Apply regression, time-series analysis, and supervised and unsupervised machine learning techniques.
• Work with partners to identify data fields, sources, and integration requirements.
• Assess data quality, provenance, and suitability for modeling.
• Identify and communicate relevant trends and patterns within complex datasets.
• Document data processes, methodologies, and models.

Required Qualifications

• Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidates must also be able to obtain and maintain the security clearance required for the role.

• MSc or PhD degree in applied mathematics, statistics, or a related field, or equivalent relevant work experience.

• 4+ years of experience applying statistical modeling and analytics, including advanced classification and regression modeling, generalized linear and multilinear regression, logistic and multinomial regression, and time-series analysis.

• Hands-on experience with supervised learning (classification and regression) and unsupervised learning (clustering and dimensionality reduction), with a strong record of applied data analysis.

• 4+ years of professional proficiency using R or Python for data wrangling and model development, along with experience using SQL or Spark SQL, database design concepts, and cloud platforms such as AWS, Azure, or Google Cloud.

• Demonstrated proficiency in statistical analysis, data visualization, data quality assurance, data management, and the development and documentation of analytical models, algorithms, methodologies, and processes.

• Ability to collaborate with stakeholders, translate requirements into data science solutions, provide technical guidance, and communicate complex analytical concepts clearly to technical and non-technical audiences.

• Strong organizational and project-management skills, with the ability to manage multiple priorities accurately and on schedule; must be local to the Vienna, VA area and able to work on-site three or more days per week, with hybrid opportunities at the supervisor’s discretion.

Preferred Qualifications

• 3+ years of experience in the aviation or aerospace industry.

• AWS or Google Cloud Professional or Specialty Certification, or the ability to obtain certification, highly preferred.

• Experience with supply chain management data systems and technologies, including ERP, Transportation Management Systems (TMS), and Warehouse Management Systems (WMS).

• Experience supporting DoD and/or VA missions and/or working in a consulting environment.

• Experience with software development processes and modern AI and machine learning technologies, including Retrieval-Augmented Generation (RAG), embeddings, vector databases, Hugging Face Transformers, BERT, BART, and large language models (LLMs).

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• Life Insurance
• 401(k) Retirement Plan with matching
• Paid Time Off
• Paid Federal Holidays