Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Sales Operations Analyst

Morningstar, Inc.
London
6 months ago
Applications closed

Related Jobs

View all jobs

Farming Operations Data Analyst

Farming Operations Data Analyst

Data Analyst, Business Intelligence Data Analyst

Farming Operations Data Analyst

Data Analyst - Commercial Operations

Senior Data Scientist - Data.One

About Morningstar:Morningstar is a leading global provider of independent investment insights, serving both individual and institutional investors across public and private markets. Our offerings include a wide range of data, research, and investment management services, with $300+ billion in assets under management. Operating in 32 countries, Morningstar supports financial advisors, asset managers, retirement plan providers, and more with comprehensive investment solutions.

The Role:We are seeking a highly skilled Business Intelligence (BI) Analyst with a strong background in finance to join our dynamic team. The ideal candidate will possess deep expertise in financial analysis, reporting, data visualization, and documentation, with proficiency in using Tableau. This role is critical in guiding decisions through data-driven insights across the organization by providing actionable insights, comprehensive financial reporting, and well-documented data sources and definitions.

What You'll Do

  • Financial Data Review:
    • Collect, review, and interpret data to support strategic decision-making.
    • Perform in-depth financial modellng, forecasting, and variance analysis.
    • Identify trends, risks, and opportunities within our datasets.


  • Reporting & Visualization:
    • Develop, maintain, and optimize Tableau dashboards to visualize complex financial data.
    • Create and distribute regular financial reports and ad-hoc analyses to stakeholders.
    • Translate business requirements into technical specifications for Tableau reporting.


  • Data Management & Documentation:
    • Ensure data accuracy and integrity by working closely with data engineering teams.
    • Manage and maintain financial data within BI systems.
    • Document data sources, definitions, and methodologies for key financial metrics and data points.
    • Develop and maintain a data dictionary to ensure consistency and clarity across the organization.
    • Design and implement data quality checks and validation procedures.


  • Collaboration & Communication:
    • Collaborate with sales, product, finance, and other departments to understand data needs and provide tailored solutions.
    • Present insights and recommendations to senior management in a clear and concise manner.
    • Support our teams during budgeting and forecasting processes by providing data-driven insights.


  • Process Improvement:
    • Identify opportunities to enhance BI processes and tools.
    • Help develop and automate processes for reporting, analysis, and documentation to improve efficiency and accuracy.
    • Stay updated on industry trends and best practices in BI, finance, and data visualization.


Who You Are

  • Education:
    • Bachelor's degree in Finance, Economics, Business Administration, Data Science, or a related field.
    • A Master's degree or relevant certifications (e.g., CFA, CPA, Tableau, Salesforce) is a plus.


  • Experience:
    • Experience in business intelligence, financial analysis, or a related field. We're expecting this role to suit people who have a few years of experience in this field
    • Proven experience with Tableau and other BI tools (e.g., Power BI, SQL).
    • Strong understanding of financial concepts. Knowledge of investment information and databases is a big plus.
    • Experience in documenting data sources and defining data points.


  • Technical Skills:
    • Strong understanding of Salesforce and reporting in Salesforce.
    • Proficiency in Tableau for data visualization and reporting.
    • Advanced Excel skills, including pivot tables, VLOOKUP, and financial modeling.
    • Familiarity with SQL and data querying techniques.
    • Experience in documenting and maintaining data dictionaries or similar documentation.


  • Soft Skills:
    • Excellent communication and presentation skills.
    • Ability to work collaboratively in a cross-functional team environment.
    • Self-motivated with a proactive approach to learning and improvement.


Ready to Shape the Future?At Morningstar, every hire we make strengthens our mission to empower investor success. Apply now and help shape the future of investing with us.

Morningstar's hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We've found that we're at our best when we're purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

301_MstarEurLtd Morningstar Europe Ltd (UK) Legal Entity

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Jobs

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.