Data Scientist
Elder Research
Arlington, VA
Job Title: Data Scientist LOCATION: ARLINGTON VA / WASHINGTON DC (DUE TO CUSTOMER REQUIREMENTS YOU MUST BE LOCATED IN THE GREATER WASHINGTON DC AREA) Workplace: Hybrid Clearance Required: Must have a IRS Public Trust w/a Full Background Investigation Requisition Type: Pipeline – this is not a current opening but rather a talent pipeline for Data Analyst of all levels with an IRS Public Trust w/ background investigation interested in supporting the Government customer. When new IRS Data Scientist positions become available, this talent community will be the first place our recruiters look to fill the roles . Candidates with profiles in this talent community can also expect to receive regular updates on relevant new job opportunities. Be sure to also apply to any relevant current funded/awarded openings, if available. Position Overview As a Data Scientist , you will work directly with clients, managers, and technical staff to understand business needs, develop technical plans, and deliver data-driven analytical solutions that solve client problems. You will primarily create and deploy predictive models from a wide variety of data sources and types using the latest mathematical and statistical methods and other emerging technologies. Position Requirements Required Clearance: Must have a IRS Public Trust w/a Full Background Investigation Required Education: Bachelor of Science degree in a relevant field (statistics, business, computer science, economics, mathematics, analytics, data science, social sciences, etc.,) Required Skills / Experience
- Exploring, cleaning, and wrangling data to provide value-added insights and identify business problems suitable for Data Science solutions
- Experience across the spectrum of design, develop, test, and implement quantitative and qualitative Data Science solutions that are modular, maintainable, resilient to industry shifts, and platform-agnostic
- Demonstrated experience using statistical and analytical software (including but not limited to Python, R, and SQL)
- Analyzing events across government, financial industries, law enforcement, and other similar data environments prioritizing them by compliance and business risk and displaying the results in evidence-driven monitoring and decision support tools.
- Experience in quantitative statistical approaches to anomaly detection to identify non-compliance risk, fraud, and cyber threats using data discovery, predictive analytics, trend analysis, assessment, and appropriate contemporary and emerging analytical techniques.
- Ability to conduct rigorous quantitative data analysis on very large quantitative data sets to develop insights and develop actionable recommendations due to previous experience developing strategies, performing assessments, gap analyses, and making actionable recommendations
- Contribute to meetings and discussions with clients and co-workers to refine understanding of the business problem at hand
- Trying different predictive modeling approaches to identify the best fit for a given set of business understanding, available data, and project timeline
- Writing modular, understandable, re-usable code within an iterative development process that includes team-based code review, client discussions, and end-user training
- Applying statistical tests for robustness, sensitivity, and significance to test and validate supervised and unsupervised models
- Preparing presentations, writing reports (technical and non-technical), and working to communicate technical results to clients with varying levels of analytic sophistication
- Ability to work autonomously in a collaborative, dynamic, cross-functional environment
- Demonstrated business savvy with solid interpersonal and communication skills (written and verbal).
- Experience with design and delivery capabilities with proficiency in gathering requirements and translating business requirements into technical specification.
- Bachelor of Science degree in a relevant field (statistics, business, computer science, economics, mathematics, analytics, data science, social sciences, etc.,)
- 1+ years of experience in data science, data analytics, or a related technical field
- Prior computer programming experience, preferably in a language such as Python or R
- Experience with data exploration, data munging, data wrangling, and model development in R or Python
- Experience using version control (e.g. git, svn, Mercurial) and collaborative Basic understanding of relational database structure and SQL
- Humble and willing to learn, teach, and share ideas
- Experience engaging and interacting with clients, stakeholders and subject matter experts (SMEs) to understand, gather and document requirements
- Comfortable learning new things and working outside of your comfort zone
- Technical mindset – you are not afraid of math!
- Must currently possess a Public Trust clearance
- Travel to and work on-site at clients both local and non-local. Number of days at client site vary depending on project requirements.
- Advanced degree (MS or PhD) in a relevant field (e.g., statistics, computer science, business, mathematics, analytics, data science, engineering, physics, social sciences, management information systems, or decision science, etc.,)
- Programming techniques (e.g. pair programming, code reviews)
- Experience with containerization and environment management (venv or conda)
- Experience with Natural Language Processing (NLP) and advanced text mining techniques
- Experience with graph analytics and network analysis
- Experience with one or more technologies such as R Shiny, Databricks, AWS, Azure
- Experience applying robust, established and emerging quantitative & statistical techniques, knowledgeable on the underlying theoretical and architectural frameworks in the fields of applied analytics, and statistical analysis to include: sampling considerations & survey design like construct validity, measurement bias, as well as internal & external validity, statistical weighting techniques, approaches to outlier and missing data, and exploratory data analysis, cross-sectional analysis, and longitudinal forecasting
- Experience implementing data science processes in a remote, austere environment to include using bash
- Experience with business intelligence and data visualization platforms (Power BI, Tableau, etc.,)
- Understanding of the data analytics lifecycle (e.g. CRISP-DM)
- Competitive Salary and Benefits
- Important Work / Make a Difference supporting U.S. national security.
- Job Stability: Elder Research is not a typical government contractor, we hire you for a career not just a contract.
- People-Focused Culture: we prioritize work-life-balance and provide a supportive, positive, and collaborative work environment as well as opportunities for professional growth and advancement.
Posted 2026-01-02
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