The Role

• Drive advanced financial data analysis and analytical modeling to support key operational areas, while reinforcing robust data governance, analytical control frameworks, and strategic decision-making support across the organization.
• Acquire, structure, analyze, and translate complex financial and operational data sets into actionable insights to drive data-informed business strategies.
• Support Business Unit in Advanced Analytics, Financial Planning and Analysis (FP&A), including tasks related to Planning, Reporting, scenario modelling and Financial Analysis.
• Develop and maintain dynamic revenue and expense models, and analytical tools to identify trends, early indicators for both risks/opportunities and predict performance outcomes.
• Emphasize reporting on Business Unit performance, focusing on revenue and applying statistical methods to interpret underlying business drivers.
• Architect and execute data-driven analysis on the annual budget, while providing regular updates through monthly and quarterly analyses like Outlook and Latest Estimates (LEs) and contributing to the 3-year Vision and Strategy Plan (VSP). Additionally, conduct ad-hoc exploratory analysis as required to support and drive emerging business needs.
• Support the month-end financial reporting process including generating reports to ensure accurate closing of monthly financials and closing in-depth financial reporting and variance analysis.
• Provide operational and business insight for key metrics across multiple functional areas.
• Provide technical insights and analytical support across functional domains by identifying trends, correlations, and causal relationships in key business metrics.
• Lead initiatives to automate data collection and optimize the design of analytics infrastructure, tools, and visualizations.
• Drive strategic initiatives that drive growth and operational improvements.
• Foster cross-functional relationships and contribute to the resolution of complex business issues through advanced analytical approaches.

Key Responsibilities

Revenue Management

• Evaluate and monitor revenue across product segments using advanced analytics and data modelling.
• Apply statistical analysis and data science techniques to assess volume trends, customer usage behaviour, and market dynamics to forecast revenue and pinpoint opportunities for optimization.
• Collaborate with sales, product management, and finance teams to align revenue and sales goals with business strategies.
• Leverage technology to enhance financial analysis and reporting. Work with large datasets and use programming or scripting (e.g. SQL, Python) to gather, cleanse, and analyze data from various systems (finance databases, CRM, etc.).

Analytical Forecasting & Planning

• Develop robust forecasting models using historical patterns, vendor invoices, and volume trends; apply predictive analytics, AI/ML based forecasting to monitor variance and how actuals are tracking to proposed forecasts
• Manage and analyze the cost structure and budget for the product management function by forecasting personal costs, overseeing 3rd party spend, and identifying budget risks and opportunities using sensitivity analysis and what-if modelling.

Business Intelligence and Performance Optimization

• Contributing to identifying business unit opportunities and challenges for enhanced performance. Collaborating with leaders to Identify and quantify performance drivers, business models and gaps through advanced data analytics; identify new business models and workflows, contributing to building business cases for necessary investments and strategic plans.
• Collaborate with sales and business leaders to drive strategic goals and benchmarks through analysing, forecast, and identifying risks and opportunities within the sales to revenue generation of our transactional products

Cultivating Expertise and Upholding Corporate Integrity

• Representing by actively developing comprehensive knowledge of products, industry trends, and business and financial acumen. This includes effective communication in various formats, upholding corporate values, fostering positive relationships with customers and colleagues, and maintaining a reputation for competence, integrity, and professionalism.

Education:

• Minimum: Bachelor’s degree in finance accounting, or data analytics/data science or economics.
• Preferred: Master’s Degree/MBA in finance or Data Science or economics

Experience, Knowledge, and Tools:

• 4 years of experience in an analytical finance, data science, or business intelligence role
• Minimum Experience/Knowledge: Finance, Data Science/Analytics, or consulting experience, including:
• Proven experience in financial and data analytics, with exposure to predictive modelling, scenario planning, and performance measurement
• Ability to meet tight deadlines and deliver quality results.

Preferred Knowledge:

Technical Skills:

• Proficiency working with large, structured and unstructured datasets
• Advanced Excel modelling (nested logic, array functions, statistical formulas)
• Strong skills in querying and scripting (SQL, Python) and familiarity with data pipelines and AI/ML based forecasting.
• Tagetik, PowerBI, and Great Plains experience is a plus.

Soft Skills:

• Self-motivated, works independently, and manages deadlines.
• Comfortable with ambiguity
• Guidance will be provided, but this is a new area, meaning not every step will be clearly defined.
• Flexibility/adaptability:
• Understand different levels of detail needed for different audiences and adapt accordingly.
• Be open to potential role changes.
• Strong written and verbal communication skills:
• Able to write documents seen at the highest levels of the company. Strong grammar, spelling, and general ability to write bullets is a must.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.