Data Scientist for Shipping Analytics - S&P Global Market Intelligence

S&P Global Market Intelligence is seeking a talented Data Scientist to join our analytics team. You will play a crucial role in developing and maintaining products that provide key insights into industry trends, specifically within the shipping analytics domain. This position involves applying advanced machine learning and statistical techniques to proprietary and open data sources. You will collaborate closely with product managers, industry analysts, and technology experts to deliver impactful products that meet customer requirements within agreed timelines.

Key Responsibilities:

• Contribute to the development and deployment of new analytics products as part of a dedicated team in Bangalore, Hyderabad, or Gurugram.
• Work effectively as an individual contributor while also collaborating seamlessly within a team environment.
• Engage in complex analytical projects, leveraging data science and engineering expertise to enhance existing or create new data products.
• Provide rapid analysis, model development, and quality assurance to support product development, consulting engagements, and client presentations.
• Develop a deep understanding of the Maritime industry and its intricate connections with economic and policy decisions.
• Collaborate with research and product management teams, incorporating their input to drive product innovation and development.

Qualifications:

Essential:

• 2-3 years of professional or research experience in a Data Science/Engineering team.
• 1-2 years of experience in time series forecasting.
• 1+ years of experience with cloud platforms like AWS or Databricks.
• 1+ years of experience working with Big Data tools such as Spark, PySpark, Cassandra, or MongoDB.
• Proven experience managing end-to-end analytics projects, from initial requirements analysis through to final deployment.
• Proficiency in performing complex data analysis and statistical modeling using R/Python and/or Spark.
• Solid understanding of RDBMS concepts and experience with SQL.
• Familiarity with data visualization principles and experience with tools like Tableau.
• Master's degree in a quantitative field (e.g., Computer Science, Mathematics, Econometrics, Engineering, Data Science).
• In-depth knowledge of forecasting techniques (e.g., S/ARIMA/X) and practical experience implementing forecasting packages in R and Python.
• Excellent knowledge of Statistics, Machine Learning algorithms, Deep Neural Networks, and Data Mining.

Beneficial:

• Experience working with geo-spatial data and/or unstructured data at scale.
• Experience with other statistical packages such as SPSS or Eviews.
• Prior experience in the Maritime Industry.

Personal Attributes:

• Strong logical thinking and problem-solving abilities.
• Excellent communication skills, with the ability to confidently present technical solutions to diverse stakeholders.
• Exceptional teamwork and interpersonal skills, with a talent for building strong professional relationships.