LMI is seeking an expertCentralized Data Managerto join our dynamic and complex United States Postal Service (USPS) portfolio. We need a candidate who excels at organizing, analyzing, and communicating data from different projects for various stakeholders, including C-suite members. This candidate should have extensive experience utilizing advanced data organization and analysis tools including Python, SQL, Databricks, Power Automate, and other Power Apps.

The ideal candidate will have experience and interest in using AI and Machine Learning tools to aid in their work and deliver excellence for the client. This role requires someone who can work with different project stakeholders to synthesize their data needs, visualize those needs, and be prepared to answer complex questions from other vendors and the client. This person will act as the centralized data SME for all data related to ongoing projects. The candidate should have experience supporting government contracts, working directly with customers, and handling sensitive data.

Responsibilities may include:

• Identifying and organizing data sources, often housed in Databricks, for all projects that LMI handles within the USPS framework.
• Working with project managers to organize their data, develop data hygiene practices, and create a framework for updating and visualizing their data to ensure it meets client needs.
• Analyzing data using advanced tools to exceed client expectations and maintain data accuracy and relevancy.
• Learning how to use new data sources and tools to ensure LMI and our project team stay current on USPS data trends and policy.
• Assisting project managers with answering complex questions related to their projects using the data that you maintain and monitor.
• Demonstrating a willingness to try new AI/ML tools that will enhance your ability to complete tasks and deliver excellence to our USPS client.

Education & Experience

• Bachelors degree in Data Science, Statistics, Computer Science, Information Systems, Business Analytics, or a related field.
• At least 3 years of professional experience in a data-focused role (e.g., data manager, data analyst, business intelligence analyst, or similar).
• Demonstrated experience working with multiple projects or departments and consolidating data from different sources.

Technical Skills

• Proficiency in working with relational databases and writing queries (e.g., SQL).
• Experience with data visualization tools (e.g., Power BI, Databricks, or similar).
• Strong Excel skills (pivot tables, lookups, basic formulas, charts).
• Experience with basic data modeling and data cleaning/validation techniques.
• Familiarity with at least one scripting language for data manipulation (e.g., Python, R), or a strong willingness to learn quickly.
• Understanding of data quality, data governance, and version control practices.
• Ability to create and maintain clear, well-documented data structures, dashboards, and reports.

Analytical & Conceptual Skills

• Ability to translate business questions from project teams and clients into clear data requirements and metrics.
• Strong analytical and critical-thinking skills to interpret data, identify trends, highlight insights and risks, and answer stakeholder questions.
• Ability to design and track KPIs, dashboards, and reports that directly address client needs.

Other

• Must be able to obtain a Position of Public Trust Clearance  US Citizen or Permanent Resident (Green Card holder).

Preferred Skills/Experience

• PMP certification.
• Project management consultancy experience supporting program operations across large, complex projects/portfolios.
• Experience with/certification in SAFe, Prosci, Lean Six Sigma, CPBA, or LUMA.
• Human-Centered Design (HCD) certification.
• Excellent working knowledge of AI/LLM prompt engineering, Machine Learning, and AI-enabled development.

Target salary range: $100,000-$140,000

Disclaimer: The salary range displayedrepresentsthe typical salary range for this position and is not a guarantee of compensation. Individual salaries aredeterminedbyvarious factorsincluding, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

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