Senior Data Analyst

System One; Vienna (VA); Hybrid; USD 55,000 - 110,000; Part time

Job summary

System One is seeking a Senior Data Analyst in Vienna, VA for a hybrid, contract role. You will partner with stakeholders to understand data needs, perform data collection and cleaning, and support BI and data science initiatives with analytical outputs.

You will use SQL, Python or R, and advanced preprocessing techniques to deliver reliable insights and maintain data quality. The position emphasizes collaboration, statistical modeling, and data governance, with opportunities to lead small

Qualifications

• 4–7 years of experience in data analysis and reporting.
• Strong understanding of business data needs and data governance.
• Proficiency with SQL, Python or R and data preprocessing techniques.

Responsibilities

• Collaborate with stakeholders to elicit data requirements and data definitions.
• Perform data collection, cleaning, validation, and quality audits.
• Analyze large datasets to support BI and data science projects.
• Develop and maintains statistical models and descriptive analyses.
• Identify data quality issues and implement cleansing and anomaly detection.
• Produce descriptive statistics and reports for decision making.
• Support data science teams and collaborate on ad hoc analyses.
• Lead small projects and coordinate with cross-functional teams.

Skills

SQL

Python

R

Data cleaning

Statistical analysis

AI tools

Data governance

PowerBI

PySpark

Data analysis

Education

Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or similar quantitative field

Tools

PowerBI

PySpark

Job description

Senior Data Analyst

Location: Vienna, VA (Hybrid)
Pay Rate: Open to Both C2C and W2 options
Position Type: Contract

Description

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

• 4-7 years of 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 AI 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

Ref: #851-Rockville-S1