Senior Data Scientist
Position Overview
SteerBridge is looking for a Senior Data Scientist to evaluate multi-dimensional aviation global supply chain and operational data to construct and maintain predictive models. Candidates must be familiar with multiple types of data models including, but not limited to, generalized linearand multilinear regression, logistic and multinomial regression, and time series analysis.
Candidates must have hand-on experience with supervised (classification, regression) and unsupervised learning (clustering, dimension reduction).
The Senior Data Scientist must be prepared to dive deep into disparate data from multiple sources in multiple formats in order to integrate and evaluate to determine the most appropriate modeling approach. The Senior Data Scientist will be responsible for leading end-to-end analytical models and data science framing activities, including but not limited to working with partners to identify fields, data provenance and integration, data quality assessments, and documentation of data processes and models.
The Senior Data Scientist must be able to review and understand large sets of data while being able to highlight relevant trends and patterns. The ideal candidate is a quick learner, curious, innovative, results-oriented and has strong interpersonal skills.
Key Responsibilities
- Collaborate with various stakeholders to understand requirements and translate those requirements into data science solutions.
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Provide guidance on best practices and industry standards across data science and analytics, data visualization, and share expertise to improve technical capabilities of the team.
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Design, develop, and integrate templates, data, and models for repeatability.
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Develop and implement data quality assurance and management protocols.
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Create, maintain, and organize technical documentation for all data collection, cleaning, and analyses.
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Location: Must be local to the Vienna, Va area and able to work on-site at our Vienna, VA office (3 + days/week). Hybrid opportunities at supervisors' discretion.
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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.
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M.S. or Ph.D. in Applied Mathematics, Statistics, or a related field; alternatively, a Bachelor’s degree in a relevant discipline with equivalent professional experience.
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6+ years of experience applying statistical modeling and analytics, including advanced classification, regression, generalized linear and multilinear regression, logistic and multinomial regression, and time-series analysis.
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Hands-on experience with supervised learning, including classification and regression, and unsupervised learning, including clustering and dimensionality reduction, with a strong record of applied data analysis.
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6+ years of professional proficiency using R or Python for data wrangling and model development, with experience using SQL or Spark SQL, database design concepts, and cloud platforms such as AWS, Azure, or Google Cloud.
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Demonstrated proficiency in statistical analysis, data visualization, data wrangling, and documenting analytical methodologies, algorithms, and implementations across a variety of tools and data platforms.
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Strong organizational and communication skills, with the ability to manage multiple projects accurately and on schedule and communicate complex analytical concepts effectively to diverse audiences.
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AWS or Google Cloud Professional or Specialty Certification, or the ability to obtain certification, highly preferred.
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Proficiency in integrating and interfacing with software development processes.
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Consulting experience.
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Experience with 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
Source: the employer's careers page. Last checked 2026-09-30. Posted 2026-06-23.