Role Overview

As a Data Scientist, you will play a key role in building and managing analytical, predictive, and data-driven capabilities across market intelligence, operational performance, commercial insights, and organizational analytics. The role involves developing scalable data systems, predictive models, dashboards, and automation solutions to strengthen business decision-making and support the organization's digital transformation initiatives.

Key Responsibilities:
Design and manage unified, structured databases across market, operational, and organizational datasets.
Build scalable, analytics-ready data pipelines and improve data integrity, standardization, and enterprise-wide data accessibility.
Develop statistical and predictive models for market forecasting, pricing intelligence, fuel and bunker trends, voyage economics, and operational performance.
Conduct trend analysis, correlation studies, and scenario modelling to generate actionable business insights.
Collaborate with Finance and Strategy teams to support business planning, risk management, and board-level reporting.
Build dashboards and decision-support tools using Power BI and AI-based analytics platforms.
Drive automation across reporting and analytics workflows to improve efficiency and accuracy.




Apply machine learning techniques to enhance forecasting accuracy, analytical capabilities, and decision-making speed.
Work closely with Chartering, Operations, Technical, Strategy, Finance, and Derivatives teams to understand business requirements.
Translate business challenges into scalable analytical solutions and present insights effectively to senior leadership.

Requirements
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related field.
Minimum of 5 years of hands-on experience in analytics, data engineering, and business intelligence.
Solid proficiency in SQL, Python, and data visualization tools such as Power BI or Tableau.
Practical experience in machine learning, statistical analysis, and predictive modelling.
Familiarity with APIs, cloud databases, and workflow automation tools.
Exposure to the shipping, logistics, or commodities industry will be an advantage but is not mandatory.
Solid analytical thinking, problem-solving, and stakeholder management skills.
Ability to work independently, manage multiple priorities, and translate complex data into meaningful business insights.

📌 Data Scientist Data Engineering Python & Sql Business Intelligence Mumbai
🏢 Sea and Beyond
📍 Mumbai