Data Scientist – Finance Analytics

Roles and Responsibilities 

Analysis & Problem Solving 

Analyze large, complex datasets such as demographics; rewards, performance, engagement, talent, learning, organization design etc with business datasets where required  

Analyze large amounts of data to identify trends & patterns to generate insights that help inform Finance Strategies 

Design & implement experiments to test multiple Hypotheses regarding the effectiveness of Finance with a view to solving specific problems that bottleneck processes or impede decision-making 

Data Quality & Accuracy 

Ensure Data Quality, accuracy & completeness in all analysis & reports 

Work with Finance Domain specialists & Data Engineers, IT & Strategic partners to build in relevant decision rules, data quality standards & data security & governance protocols in the Data Lake being developed 

Collaborate with relevant stakeholders to develop a Finance Data architecture that is reliable & secure 

Process Assurance & Efficiency 

Identify opportunities to streamline and automate Finance processes to drive process efficiency by leveraging Data & Technology 

Ensure Workflow Based Decision Assets are suitably embedded through the use of new & emergent technologies (AI/ML/RPA) 

Develop Use Cases in priority areas to demonstrate success & replicability 

Modelling & Deployment 

Develop predictive models to identify trends & patterns, forecast outcomes & inform Finance & Business Decisions around workforce trends & patterns such as turnover rates; retention; engagement; hiring of best-fit talent; workforce planning etc 

Build & deploy AI/ML models to optimize decision-making & drive value  

realization across Talent Attraction; Talent Sustainability & Talent Development  

Skill and Experience 

3+ years of experience in data analysis, modelling, data mining & visualization 

Strong analytical & problem-solving skills with the ability to think critically & creatively about complex business problems 

Proficiency in statistical analysis & advanced ML modelling techniques including prediction, forecasting techniques.  

Good understanding of techniques like regression analysis XgBoost, Neural Network, machine learning & data mining 

Expertise in balancing data set and strong statistics fundamentals 

Expertise in data visualization & reporting tools such as Power BI & Tableau 

Strong Programming skills in languages such as Python, R or SQL and good understanding of model libraries 

Expertise in resource optimization for running models as well as good understanding of MLOps 

Good understanding of Gen AI 

Good understanding of cloud AI platforms component to run the models and pipelines like Vertex AI / BigQuery ML / Auto ML / Gemini API (in case of GCP) or ML Studio / Co Pilot / Azure Open AI (in case of Azure) etc. 

Understanding of Finance processes, the data sets and data domains of Finance, typical AI/ML interventions in the Finance Processes – Invoice to Pay, Record to Reports, Credit to Cash, Intercompany, Treasury and Fixed Assets. 

Understanding of common ERPs and related systems like SAP FICO and COPA is preferred. 

Excellent communication skills, with the ability to clearly & persuasively communicate complex data insights to non-technical audiences 

Ability to work independently & collaboratively and to manage multiple projects & priorities simultaneously 

Familiarity with Finance Systems & Technologies as well as understanding the impact of new & emergent tools & technologies ie Generative AI & Machine Learning