Data Analytics Senior Manager - Finance

Engineering · Full-time · Global

Job description

Animoca Brands, a Deloitte Tech Fast winner and ranked in the Financial Times list of High Growth Companies Asia-Pacific 2021, is a leader in digital entertainment, blockchain, and gamification that is working to advance digital property rights. It develops and publishes a broad portfolio of products including the REVV token and SAND token; original games including The Sandbox, Crazy Kings, and Crazy Defense Heroes; and products utilizing popular intellectual properties including Disney, WWE, Snoop Dogg, The Walking Dead, Power Rangers, MotoGP™, and Formula E. The company has multiple subsidiaries, including The Sandbox, Blowfish Studios, Quidd, GAMEE, nWay, Pixowl, Forj, Lympo, Grease Monkey Games, and Eden Games. Animoca Brands has a growing portfolio of more than 200 investments in NFT-related companies and decentralized projects that are contributing to building the open metaverse, including Axie Infinity, OpenSea, Dapper Labs (NBA Top Shot), Yield Guild Games, Harmony, Alien Worlds, Star Atlas, and others. For more information visit or follow on Twitter or Facebook.

Job Summary: We are seeking an experienced Data Analytics Senior Manager with expertise in finance to lead our data analytics initiatives. In this role, you will be responsible for collecting, analyzing, and transforming raw financial data into actionable insights that drive informed decision-making. You will collaborate closely with cross-functional teams, including finance, IT, and business operations, to understand data requirements and develop robust analytics solutions. Your expertise in data manipulation and integration will be instrumental in refining finance data and seamlessly plugging it into our finance system.


  • Lead the design and implementation of data analytics strategies and frameworks to support finance functions, including financial planning, budgeting, forecasting, and financial reporting.
  • Develop a deep understanding of the company's finance systems, data sources, and information flow, identifying opportunities to enhance data quality, accuracy, and integrity.
  • Collaborate with finance and IT teams to define data requirements, validate data sources, and ensure data consistency across systems and platforms.
  • Create and maintain data models, data dictionaries, and data transformation rules to structure and refine raw finance data into usable formats.
  • Develop and implement data cleansing and validation procedures to ensure the accuracy and reliability of financial data.
  • Build and maintain robust data analytics tools, dashboards, and reports to enable self-service analytics for finance and business stakeholders.
  • Perform advanced data analysis, including statistical analysis, trend analysis, and predictive modeling, to uncover insights and patterns in financial data.
  • Stay updated on emerging trends and best practices in data analytics and financial technology, incorporating relevant advancements into the company's data analytics capabilities.
  • Ensure compliance with data privacy and security regulations, implementing appropriate measures to protect sensitive financial data.


  • Bachelor's degree in Data Analytics, or a related field; advanced degree preferred.
  • 8+ years of experience in data analytics
  • Strong knowledge of finance principles, financial systems, and financial data structures.
  • Advanced proficiency in data manipulation, transformation, and integration using tools such as SQL, Python, R, or similar languages.
  • Experience with data visualization tools, such as Tableau, Power BI, or similar platforms, to develop interactive dashboards and reports.
  • Solid understanding of statistical analysis and predictive modeling techniques.
  • Strong analytical and problem-solving skills, with the ability to translate complex financial data into actionable insights.
  • Excellent project management skills, with the ability to prioritize and manage multiple initiatives effectively.
  • Strong communication and presentation skills, with the ability to convey complex data analysis results to non-technical stakeholders.