Job Responsibilities:
- Analyzes multifaceted and high-dimensional data problems, developing innovative solutions, formulating sophisticated hypotheses, creating advanced proof of concepts to validate & refine analytical models and implement solutions to business problems.
- Participates in end-to-end data mining projects, utilizing advanced algorithms, machine learning models, and AI techniques to extract deep and actionable insights from complex, large-scale data sources.
- Executes the deployment and rigorous testing of data science solutions and insights, ensuring optimal performance, scalability, and seamless integration with existing enterprise systems and workflows.
- Presents complex data-driven insights and strategic recommendations to senior stakeholders, effectively translating intricate analytical results into clear, actionable business strategies and influencing key decision-making processes.
- Monitors, maintains, and continuously improves the performance of deployed models, conducting regular reviews, updates, and optimizations to ensure sustained accuracy, relevance, and business impact.
- Interacts and collaborates with cross-functional teams, including IT, data engineering, and various business units, to ensure the successful operationalization, integration, and scaling of data science solutions across the finance function.
- Build data-science and technology based algorithmic solutions to address business needs
- Design large scale models using Regression, Linear Models Family, Time-series models.
- Drive the collection of new data and the refinement of existing data sources
- Analyze and interpret the results of analytics experiments
- Applies a global approach to analytical solutions-both within a business area and across the enterprise
- Ability to use data for Exploratory, descriptive, Inferential, Prescriptive, and Advanced Analytics
- Ability to share dashboards, reports, and Analytical insights from data
- Experience of having done visualization on large datasets – Preferred – added advantage Technical Knowledge and Skills required
- Experience solving analytical problems using quantitative approaches
- Passion for empirical research and for answering hard questions with data
- Ability to manipulate and analyze complex, high-volume, high-dimensionality data from varying sources
- Ability to apply a flexible analytic approach that allows for results at varying levels of precision
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- Expert knowledge of an analysis tool such as Pyspark and Python.
Minimum required Education:
Bachelor's / Master's Degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.
Minimum required Experience:
Minimum 10 years of experience with Bachelor's in areas such as Data Analytics, Data Science, Data Mining, Artificial Intelligence, Pattern Recognition or equivalent OR no prior experience required with Master's Degree.
Preferred Skills:
• Data Analysis & Interpretation
• Data Governance
• Statistical Methods
• Statistical Programming Software
• Business Intelligence Tools
• Data Mining
• Machine Learning Engineering Fundamentals
• Research & Analysis
• Requirements Analysis
• Root Cause Analysis (RCA)
• Data Quality Management Systems
• Regulatory Compliance