Data Scientist II
Listed on 2026-07-20
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IT/Tech
Data Analyst, Data Scientist, Data Engineering, Machine Learning/ ML Engineer
Position Title: Data Scientist II
Location: Arlington, VA (Hybrid – Candidates must reside in the DC Metro area and report onsite twice per pay period)
Clearance Requirements: Must be a U.S. Citizen and eligible to obtain a Public Trust Clearance
Position Status: Contract
Position
Description:
Seneca Resources is seeking a highly skilled Data Scientist II to support a federal customer in developing advanced data analytics, artificial intelligence, and business intelligence solutions. This role is ideal for an experienced data professional who thrives on solving complex business problems through machine learning, predictive analytics, data engineering, and visualization. The successful candidate will work with large structured and unstructured datasets, develop scalable analytical models, and create data-driven solutions that support investigative, audit, and operational initiatives.
This position offers the opportunity to work with modern cloud technologies, AI/ML platforms, and enterprise data environments while collaborating with cross-functional technical and business teams.
- Design, develop, and deploy advanced data science, machine learning, and artificial intelligence solutions.
- Collect, extract, clean, transform, normalize, validate, and analyze structured and unstructured data from multiple enterprise data sources.
- Build predictive models, statistical models, natural language processing (NLP) solutions, and other AI-driven analytical capabilities.
- Design experiments, test hypotheses, and develop scalable analytical models to solve complex business problems.
- Develop interactive dashboards, reports, and visualizations using Power BI and other business intelligence tools.
- Create ETL processes and data pipelines supporting analytics, reporting, and machine learning initiatives.
- Develop data solutions using relational databases, data lakes, lake houses, and cloud-based analytics platforms.
- Build automation solutions using Python, SQL, R, JavaScript, and related technologies.
- Engineer proof‑of‑concept solutions and transition successful prototypes into production.
- Perform advanced statistical analysis, pattern recognition, text mining, and data mining to identify trends and actionable insights.
- Collaborate with business stakeholders to gather requirements and translate business needs into technical solutions.
- Produce comprehensive technical documentation, including solution designs, data dictionaries, user guides, test plans, and implementation documentation.
- Troubleshoot existing analytical applications and optimize performance.
- Support data governance, data quality, data security, and continuity of operations initiatives.
- Present technical findings and analytical insights to technical and non-technical audiences.
- Mentor team members and provide guidance on data science best practices and analytical methodologies.
- Bachelor's degree in Computer Science, Information Technology, Data Analytics, Statistics, Mathematics, or a related technical field.
- 5+ years of professional experience developing data science solutions using Python, SQL, R, JavaScript, or similar programming languages.
- 3+ years of experience with Machine Learning, Artificial Intelligence, Natural Language Processing (NLP), Robotics Process Automation (RPA), predictive analytics, text mining, or data mining.
- Experience developing data visualization solutions using Power BI, including DAX and Power Query (M).
- Experience designing and implementing ETL processes and data integration solutions.
- Strong experience with relational databases, SQL development, and data modeling.
- Experience working with enterprise data warehouses, data lakes, and lakehouse architectures.
- Experience with cloud-based analytics platforms including Azure or AWS.
- Hands‑on experience with Databricks, Azure Data Factory, Azure Data Lake, or similar cloud data services.
- Strong knowledge of statistical analysis, predictive modeling, and business intelligence methodologies.
- Experience developing scalable analytical models and dashboards in enterprise environments.
- Strong understanding of software development lifecycle (SDLC), testing, debugging,…
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