“CSC may exercise its option to extend the SOW beyond October 5, 2027, provided that the Master Service Agreement is extended. Any such extension shall be on the same terms, conditions, and covenants as those contained in the SOW.”

Responsibilities
1. Analyze complex data sets to generate predictive models and insights that inform business strategies
2. Uses statistical methods, machine learning, and programming languages to interpret data and provide actionable insights
3. Initiate, research, develop and manage new information studies and devise innovative statistical models for data analysis
4. Conduct initial analyses to understand data’s characteristics and identify potential patterns or trends

General Skills
1. Experience identifying business problems that can be addressed using data analysis
2. Experience identifying relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables
3. Familiarity and experience with data visualization tools e.g. Power BI
4. Experience and proficiency with data mining, mathematics and statistical analysis
5. Experience developing data-driven solutions to improve business performance and decision making
6. Experience collaborating with cross-functional teams to integrate data insights into business strategies
7. Extensive experience in pattern recognition and predictive modeling
8. Extensive experience with programming languages like Python or R
9. Experience working with big data sets
10. Experience with code version control systems such as GIT
11. Experience with database management systems
12. Project management experience
13. Awareness of emerging I&IT trends and technologies
14. Excellent analytical, problem-solving and decision-making skills; verbal and written communication skills; interpersonal and negotiation skills
15. A team player with a track record for meeting deadlines

Desirable Skills
16. Advanced degree in social science or statistics
17. Certifications such as the Data Science Professional Certificate (offered by IBM) or Google Data Engineer certification

• Skills

• Experience and Skill Set Requirements
Technical Knowledge / Skills (50%)
1. Demonstrates knowledge of information management, data management, database architecture, data governance, metadata management, master data management, data lineage, extract/transform/load (ETL) processes, data warehousing, and data integration.
2. Demonstrates knowledge of data modernization, digitization methodologies, records conversion, data quality improvement practices, and the management of structured, semi-structured, unstructured, historical, and legacy datasets.
3. Demonstrates proficiency in statistical analysis, data mining, predictive analytics, artificial intelligence, machine learning, research methodologies, and data modelling techniques.
4. Demonstrates knowledge of data analytics, including relational databases, geospatial analysis, spatial data management, data visualization, and analytical frameworks used to support business decision-making.
5. Demonstrates proficiency with Structured Query Language (SQL) for accessing, extracting, transforming, and analyzing data across multiple platforms and repositories.
6. Demonstrates proficiency using Python, R, or other equivalent tools for data analysis, modelling, automation, and data transformation.
7. Demonstrates proficiency with analytics and visualization tools such as Power BI, Tableau, R Shiny, ArcGIS, or equivalent reporting and analytical platforms.
8. Demonstrates knowledge of information management standards, data governance frameworks, accessibility requirements, and applicable GO-ITS standards.
Research, Analytical and Problem-Solving Skills (40%)
1. Demonstrates the ability to analyze and assess complex datasets to identify data quality issues such as duplicate records, inconsistencies, missing values, and invalid data.
2. Demonstrates the ability to support data migration, digitization, modernization, and information management initiatives through data analysis and quality assessment activities.
3. Demonstrates the ability to identify, assess, and document business data requirements and translate them into analytical solutions.
4. Demonstrates the ability to identify trends, patterns, relationships, and insights within large and complex datasets to support business, program, and regulatory objectives.
5. Demonstrates the ability to analyze, integrate, and interpret both spatial and non-spatial datasets to support planning, compliance, reporting, and decision-making activities.
6. Demonstrates the ability to develop and apply predictive models, analytical frameworks, business intelligence solutions, and geospatial analysis techniques.
7. Demonstrates the ability to integrate data from multiple sources and provide recommendations that support evidence-based decision-making.
8. Demonstrates the ability to apply innovative analytical approaches, emerging technologies, and industry best practices to address complex business challenges.
Communication and General Skills (10%)
1. Demonstrates strong verbal and written communication skills, including the ability to communicate complex analytical findings to technical and non-technical audiences.
2. Demonstrates the ability to prepare technical documentation, business reports, data dictionaries, source-to-target mapping documents, and data flow diagrams.
3. Demonstrates the ability to collaborate effectively with business stakeholders, information management specialists, GIS specialists, business analysts, project teams, and technical resources.
4. Demonstrates the ability to communicate analytical and geospatial findings through reports, dashboards, maps, presentations, and other visualization tools.
5. Demonstrates the ability to facilitate discussions, present recommendations, and support informed decision-making.
6. Demonstrates the ability to work effectively within multi-disciplinary teams in a complex project environment.

• Supplier Comments
Closing Date/Time: 2026-09-08, 12:00 p.m. EST
Max submission: 2 (Two)
5 days onsite


Must Have:
Demonstrates knowledge of data analytics, including relational databases, geospatial analysis, spatial data management, data visualization, and analytical frameworks used to support business decision-making.
Demonstrates proficiency with analytics and visualization tools such as Power BI, Tableau, R Shiny, ArcGIS, or equivalent reporting and analytical platforms.
Demonstrates the ability to analyze, integrate, and interpret both spatial and non-spatial datasets to support planning, compliance, reporting, and decision-making activities.
Demonstrates the ability to develop and apply predictive models, analytical frameworks, business intelligence solutions, and geospatial analysis techniques.