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Role Overview: As a Senior Data Scientist focused on FP&A, you will be responsible for developing advanced data models, conducting predictive and prescriptive analytics, and collaborating closely with stakeholders across the world to drive strategic decision-making. You will work with finance data sets, leverage statistical techniques and machine learning algorithms, and partner with internal teams and vendors to deliver actionable insights that drive business growth and profitability.

Key Responsibilities:

• Develop and implement advanced data models for financial planning, forecasting, and performance analysis.

• Conduct predictive and prescriptive analytics to identify trends, patterns, and opportunities in financial data.

• Collaborate with stakeholders across the world to understand business requirements and translate them into data-driven solutions.

• Partner with vendors and external partners to access additional data sources and enhance analytics capabilities.

• Work closely with other digital teams, including IT, Business Intelligence, and Data Engineering, to integrate data sources and deploy analytics solutions.

• Utilize Azure, Databricks, and Power BI to build scalable and efficient data pipelines, perform advanced analytics, and create interactive dashboards.

• Communicate findings and insights to senior leadership and key stakeholders through compelling visualizations, reports, and presentations, emphasizing storytelling to drive understanding and action.

• Continuously evaluate and improve data models, algorithms, and methodologies to enhance predictive accuracy and business impact.

• Stay abreast of latest developments in data science, machine learning, and finance domain, and apply best practices to drive innovation and excellence.

Qualifications:

• Bachelor’s degree in computer science, Statistics, Mathematics, Economics, Finance, or related field. Master's or Ph.D. preferred.

• 10+ years of experience in data science, with a focus on FP&A, finance data models, and predictive/prescriptive analytics.

• Proficiency in statistical analysis, machine learning techniques, and predictive modeling tools (e.g., Python, R, TensorFlow, scikit-learn).

• Strong understanding of finance concepts, financial modeling, and FP&A processes.

• Experience working with Azure services (Azure ML, Azure Synapse Analytics), Databricks, and Power BI for data processing, analytics, and visualization.

• Excellent communication and interpersonal skills, with the ability to collaborate effectively with stakeholders across different regions and functions.

• Proven track record of delivering actionable insights and driving strategic decision-making through data-driven approaches.

• Ability to thrive in a fast-paced, dynamic environment and manage multiple projects simultaneously.

• Experience working with SQL Tools, Azure Data Lake, Azure Data Factory, DevOps, Azure Databricks - Notebooks, Compute Configuration & ML Libraries. Strong experience in SQL & Python languages. Preferred Data Science certification, Languages R & Scala.

• Experience in designing data flow, data ingestion & SDLC methodologies.

• Ability to demonstrate AI & ML scenarios.