Manager, Data Science - Finance Advanced Analytics & Reporting

Job description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Data Analytics & Computational Sciences Job Sub Function: Data Science Job Category: People Leader All Job Posting Locations: New Brunswick, New Jersey, United States of America Job Description: We are searching for the best talent for Manager, Data Science - Finance Advanced Analytics & Reporting About Innovative Medicine Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at https://www.jnj.com/innovative-medicine Purpose: As a Manager, Data Science - Finance Advanced Analytics & Reporting on the Global Finance Data Science team, you will design and deliver advanced analytics, financial and operational models, trusted reporting products, and governed data solutions that improve decision-making across Finance. You will combine finance and ERP expertise with data science, business intelligence, and data engineering capabilities to translate complex business questions into scalable, explainable, and executive-ready insights. The role will advance the organization’s finance data and analytics strategy by developing predictive and diagnostic models, modernizing planning and reporting, strengthening semantic and financial data models, and embedding data quality, lineage, security, and auditability into reusable solutions. The individual will partner with Finance, FP&A, Controllership, Data, and Technology teams to reduce manual effort, improve reporting continuity, and provide leadership-ready visibility into performance, risks, trends, and opportunities. You will be responsible for: Partner with Finance, Compliance, and Controllership stakeholders to translate complex business problems into clear analytical questions, measurable hypotheses, required data points, and success criteria. Decompose finance processes and KPIs into the underlying transactions, master data, dimensions, calculations, and business rules needed to support quantitative analysis. Trace finance requirements to SAP data structures and independently identify the relevant modules, tables, views, fields, keys, hierarchies, document flows, and relationships across SAP ECC, S/4HANA, CFIN, ACDOCA, SAP BW, and related platforms. Profile, query, join, and analyze high-volume SAP financial and operational data using SQL, Python, PySpark, or similar tools to assess completeness, accuracy, granularity, availability, and fitness for purpose. Reconcile extracted data to SAP source reports, general ledger balances, subledgers, and established financial outputs; investigate discrepancies and document data lineage, transformations, assumptions, and limitations. Apply statistical analysis, exploratory data analysis, driver analysis, segmentation, forecasting, anomaly detection, and scenario modeling to uncover patterns, explain financial outcomes, and quantify risks and opportunities. Lead rapid proof-of-concept development from problem framing through data discovery, extraction, transformation, model or rule development, visualization, and validation with Finance subject-matter experts. Define POC hypotheses, scope, analytical approach, data requirements, acceptance criteria, and decision points; iterate quickly based on stakeholder feedback and demonstrate measurable business value. Convert successful POCs into clear solution recommendations, including data mappings, calculation logic, controls, architecture, scalability considerations, and a practical path to production. Communicate analytical findings, data gaps, trade-offs, and recommendations in concise business language, using prototypes, visualizations, and executive-ready narratives to align Finance and Technology stakeholders. Qualifications / Requirements Required Minimum Education and Experience: Bachelor’s degree in Computer Science, Data Science, Engineering, IT, Industrial Engineering or another quantitative or STEM discipline. A Master’s degree in a relevant field is a plus. At least 10 years of relevant experience in building advanced analytics, data science, financial modeling, enterprise solutions, or data engineering leveraging SAP data. Demonstrated ownership of complex analytics products from requirements through production adoption. Strong advanced analytics foundation, including statistical analysis, forecasting, regression, time-series methods, anomaly detection, segmentation, scenario modeling, and model evaluation. Hands-on proficiency with Python, SQL, PySpark, data preparation, feature engineering, exploratory analysis, visualization, and productionization of analytical solutions. Experience developing financial, operational, planning, forecasting, and scenario models and translating results into clear business implications. Strong knowledge of SAP Finance data and reporting, including SAP ERP or S/4HANA, ACDOCA, CFIN, SAP BW/4HANA, SAP Datasphere, and SAP Analytics Cloud; experience with planning models, data actions, or advanced formulas is valuable. Experience with modern analytics and data platforms such as Microsoft Fabric, Power BI, Databricks, Snowflake, Tableau, or comparable technologies, including dimensional and semantic modeling. Ability to design executive-ready dashboards, KPI frameworks, and self-service analytics that make complex financial and operational performance understandable and actionable. Experience with data quality, source-to-target reconciliation, metadata, lineage, row-level security, access controls, model governance, and audit-sensitive or SOX-controlled reporting environments. Knowledge of scalable data architecture and engineering patterns, including medallion architectures, ETL/ELT, incremental processing, orchestration, testing, deployment, monitoring, reliability, and cost-performance optimization. Experience applying machine learning, generative AI, or intelligent automation to Finance use cases such as forecasting, classification, anomaly detection, root-cause analysis, data validation, or workflow automation. Strong stakeholder leadership and communication skills, with the ability to work across Finance and Technology, lead complex initiatives, mentor team members, and present recommendations to senior audiences. Preferred: Deep SAP analytics experience in global Finance, FP&A, Controllership or regulated environment; Microsoft Fabric, Power BI, Databricks, or Snowflake implementation; reporting modernization; SOX and audit readiness; and leadership of cross-functional or matrixed analytics teams. Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as define