Mars—Senior Learning Measurement Analyst

Job description

Description: Job Description: Job Purpose/Overview The Senior Learning Measurement Analyst plays a pivotal role within Mars University’s Learning Measurement team, supporting the team by managing data, analysis, and reporting to evaluate the impact of learning programs. This role combines data transformation with visualization, applying analytical techniques where appropriate to create visibility to learning effectiveness and business value. The analyst collaborates closely with cross-functional teams to ensure data accuracy, optimize reporting processes, and deliver insights that drive continuous improvement. Key Responsibilities - Data Operations & Automation: Own the design and delivery of scalable reports and dashboards that support core learning operations (e.g., nominations, demand planning, evaluations). Continuously improve the data ecosystem by automating, standardizing, and optimizing reporting processes to enhance data usability and reduce manual effort. - Program & Portfolio Measurement: Support measurement efforts for priority learning programs, including KPI development, pre- and post-training assessment analysis, and summarizing key takeaways. Lead data support for new initiatives, such as pilots and new program launches. - Insights & Added Business Value: Take a consultative approach to data requests, helping stakeholders define their needs and shaping solutions that add strategic value. Investigate and resolve data discrepancies or broken reports independently, setting up new methods when standard procedures do not apply. - Mentorship & Partnership: Serve as a technical mentor and thought partner for colleagues within the Learning Measurement team. Act as a key liaison with partners across MGS Learning, P&O, and Functional teams to deliver accurate, relevant data and represent the Learning Measurement Strategy. - Governance & Documentation: Promote best practices in data protection, documentation, and quality control. Maintain clear documentation on how reports are built, where numbers come from, and what definitions are used. Context and Scope This role operates within the global Learning Measurement team, managing data projects from intake through to delivery with a high degree of autonomy. The analyst will partner closely with cross-functional teams and stakeholders across different segments of the business, translating technical findings into business-relevant recommendations. The position requires a structured, problem-solving mindset to uncover new and less obvious solutions that drive stakeholder impact. Job Specifications/Qualifications Bachelor’s degree in Data Science, Analytics, Statistics, Computer Science, or a related field with 3+ years of experience in data and reporting Knowledge / Experience - Strong practical experience preparing, cleaning, and combining data from multiple sources (such as SQL, Excel, or automated data flows) - Ability to run basic and intermediate statistical summaries (such as averages, standard deviations, distributions, and pre/post score comparisons) to find key insights and explain trends - Proven ability to build and maintain clean, easy-to-use dashboards in Power BI, Tableau, or similar tools - Ability to identify unusual data issues, find where things went wrong, and fix them independently - Experience supporting junior colleagues, helping them troubleshoot data issues and checking work for quality and accuracy - Experience finding manual or repetitive reporting steps and making them simpler or automated - Clear verbal and written English skills to explain data findings simply to colleagues and stakeholders - Experienced in digital fluency and demonstrated curiosity and adaptability in adopting new technologies including AI to drive innovation and continuous improvement - Experience in working with learning or HR data (e.g., training completions, program effectiveness, people data) is preferred. Skills: data analysis, dashboard development, tableau, sql, data cleaning, data transformation, statistical analysis, kpi development, data visualization, report automation, data quality control, data documentation, stakeholder management, mentorship, cross-functional collaboration, problem solving, ai adoption, learning measurement, hr data analysis