Senior Analyst in FP&A for CINPAL, providing financial insights and tools to support strategic decision - making in a growing metalworking industry. Actively collaborating with various departments.
About the role
- Supports the evaluation and enhancement of learning programs at Multiverse through data insights. Involves data preparation, program health analysis, and collaboration with stakeholders.
Responsibilities
- Gather requirements from key stakeholders across Learning to identify core questions and utilise the appropriate data sources for ongoing analysis of our learning programs.
- Support the business with bespoke reporting and data preparation for regulatory inspections (e.g., Ofsted) or custom client requests.
- Utilize central Data and Insights self-serve capabilities to create visualisations that promote a data-driven culture within the learning team.
- Use approved AI and analytical tooling to generate data views in Count and Metabase, running SQL queries to extract and analyze relevant data points from our data warehouse.
- Conduct regular analysis on program health to report on current state against key metrics (e.g., retention, attainment, and achievement).
- Perform reliability and validity analysis to provide recommendations to assessment design owners for data-backed improvements.
- Support grading reliability analysis of assessments (AI and human-led) to monitor consistency and ensure unbiased performance across subgroups.
- Use data to identify trends and anomalies, providing program owners with the evidence needed to improve metrics and build business cases for new initiatives.
- Create clear data visualisations to feed insights into leadership forums, enabling informed decision-making regarding apprenticeship regulatory thresholds.
- Prepare and provide structured data sets to the AI Learning Solutions Team to assist in the refinement of AI agent content and customisation.
Requirements
- Technical Proficiency: Proven data analysis and visualization skills using tools such as Excel, PowerBI/Tableau, SQL, Python, or Looker.
- Domain Knowledge: Experience or strong foundational knowledge in curriculum and assessment evaluation processes.
- Contextual Experience: Familiarity with learner and customer experience metrics, ideally within a B2B environment.
- Precision: A high degree of attention to detail and data integrity.
- Curiosity: A strong interest in how data applications can improve the efficacy of AI in learning design.
- Adaptability: Comfort working in a fast-paced environment; the ability to remain effective when faced with new challenges and to adapt as team processes evolve
Benefits
- Time off - 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year
- Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support
- Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month
- Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year
- Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that’s always stocked!
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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