Overview

Partner with business stakeholders and other analysts to understand business data needs, capture data requirements, and perform data collection, processing and cleaning. Provide inputs for complex data science and business intelligence projects and perform analytical on large data sets to support departmental and organizational objectives. Work under minimal supervision and use complete understanding of business needs and objectives to support projects that have impact on the achievement of operational goals. Advanced skill set and proficiency with procedures and analysis techniques.

Responsibilities

• Work with technology organization and business end-users to understand data and analysis needs and develop technical requirements including data definitions, business rules, and data quality requirements; conduct data UAT, and data accuracy, validation, integrity research
• Ensure compliance with deliverable reporting requirements by performing quality data audits and analysis
• Identify and compile data sets using a variety of tools to help predict, improve, and measure the success of key business-to-business outcomes
• Analyze and resolve complex data quality issues, utilizing advanced data profiling, cleansing, and monitoring techniques to maintain data integrity and reliability
• Develop and implement advanced data cleaning and validation processes, including outlier detection, imputation methods, and anomaly detection, to maintain data integrity and quality
• Clean and organize raw data and generate descriptive statistics in support of business intelligence and data science projects
• Partner with data science teams to maintain statistical models for ongoing and ad hoc review and analysis of data
• Build working relationships with team members and subject matter experts
• Lead small projects and initiatives

Qualifications

• Advanced experience in data analysis and reporting
• Complete knowledge and understanding of business area/specialization
• Skill in data manipulation and scripting languages such as SQL, Python, or R, as well as advanced data cleaning and preprocessing techniques and tools
• Effective skill with ETL tools and techniques, data cleaning, and other analytical techniques required for data usage
• Advanced skill with statistical analysis such as measures of central tendency, normal distribution, variance, standard deviation, basic tests, correlation, and regression techniques
• Advanced skill interpreting, extrapolating and interpolating data for statistical research and modeling
• Knowledge of various data structures and ability to extract data sources (e.g., PySpark, PowerBI)
• Strong understanding of data governance principles and practices
• Bachelor's Degree in Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields

Hours: Monday - Friday, 8:00AM - 4:30PM

Location: 820 Follin Lane, Vienna, VA 22180 | 5510 Heritage Oaks Drive, Pensacola, FL 32526 | 141 Security Drive, Winchester, VA 22602 | 9999 Willow Creek Road, San Diego, CA 92131

About Us