Senior Data Scientist - Finance

About the role

Hitachi Vantara's Global Analytics & Decision Sciences (GADS) team, part of the Finance organization, is looking for a Senior Data Scientist. The team connects business functions to drive growth, enable data-driven decisions and solve complex problems. The role works with stakeholders from services, sales, marketing, product, finance, pricing and partner operations, and requires submitting a resume in English.

Key responsibilities

• Work with stakeholders to understand analytical needs, frame key questions and turn them into actionable data and analytics solutions.
• Provide thought leadership in advanced analytics, including statistical analysis and descriptive, diagnostic, predictive and prescriptive modeling.
• Synthesize insights across financial performance, forecasts, products, geography, industries, competitors and customer segments.
• Design and build scalable solutions using Python, SQL, SQL Server, Oracle, AWS and Power BI.
• Lead cross-functional projects and present findings clearly to management and executives.
• Promote AI and machine learning adoption, establish best practices and scale capabilities across the team.
• Mentor junior team members and share insights with management.

Required profile

• Bachelor's degree in Statistics, Data Science, Quantitative Economics, Marketing Analytics, Mathematics, Computer Science, Engineering or a related quantitative field; Master's degree preferred.
• At least 5 years of experience as a Data Scientist or in a similar analytical, quantitative or technical role.
• Strong problem-solving and analytical skills, attention to detail and ability to adapt quickly.
• Advanced English proficiency.

Required skills

• Proficiency in Python and SQL, with data engineering, wrangling, feature engineering and scalable processing.
• Statistical analysis and machine learning (regression, hypothesis testing, dimensionality reduction, predictive modeling, data mining).
• Data platforms (SQL Server, Denodo or similar) and cloud platforms (AWS, GCP or Azure).
• Data visualization and storytelling with Power BI and advanced Excel.
• Understanding of data modeling, ML libraries and best practices.