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S&P Global

Delivers credit ratings, market data, indices

Data Scientist 3

Computer VisionConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listed

About the Job

Requirements

  • A university degree in Computer Science, Engineering, Mathematics, or a related discipline, or equivalent practical experience.
  • At least 3 years of hands-on programming experience, primarily in Python, with a strong focus on building, training, and evaluating machine-learning and deep-learning models.
  • Strong experience with machine-learning frameworks and libraries such as PyTorch, TensorFlow, Keras, and scikit-learn, including designing and implementing neural-network architectures.
  • Proven experience in computer-vision techniques and applications, including image and video processing, feature extraction, object detection, segmentation, and representation learning.
  • Experience developing end-to-end machine-learning workflows, from data preparation and feature engineering through model training, validation, and deployment, emphasizing model performance, robustness, and maintainability.
  • Working knowledge of data-storage and querying technologies, including SQL and/or NoSQL, to support analytical and machine-learning workflows.
  • Hands-on experience using cloud platforms such as AWS, Azure, or GCP for machine-learning experimentation, training at scale, and model deployment.
  • Familiarity with distributed and accelerated computing concepts relevant to machine-learning workloads, such as multi-GPU training, distributed training, or large-scale inference.
  • Experience collaborating closely with data engineers and platform teams to integrate models into production pipelines while maintaining ownership of model logic and performance.
  • Familiarity with version-control systems such as Git and best practices for collaborative machine-learning development.
  • Ability to communicate machine-learning model results, trade-offs, and limitations clearly to technical and non-technical stakeholders.

Responsibilities

  • Collaborate with stakeholders, including data scientists, analysts, engineers, and business teams, to understand data needs and translate them into actionable technical requirements.
  • Design, build, and maintain scalable data pipelines using modern tools and cloud platforms such as AWS, Azure, or GCP.
  • Develop and maintain data infrastructure for analytics and machine learning using cloud-native technologies and services.
  • Improve data quality, lineage, and reliability, and troubleshoot issues across the data lifecycle.
  • Support deployment and monitoring of analytics and machine-learning solutions in production, working closely with data-science and engineering peers.
  • Contribute to an Agile team environment through documentation, code reviews, and iterative delivery.

Desired Qualifications

  • Exposure to workflow-orchestration or experiment-management tools such as Airflow and MLflow, or similar, for reproducible machine-learning pipelines.
  • Experience with data-governance practices, including privacy, security, access controls, and compliance expectations.
  • Experience improving data observability through monitoring, alerting, service-level agreements, and incident response.

About the Company

S&P Global

Delivers credit ratings, market data, indices

S&P Global provides financial information and analytics for investors, corporations, and governments, including credit ratings, market data, and indices. It compiles large financial data, conducts research, and offers analytics, ratings, and benchmarks accessed via subscriptions, licenses, or transaction-based services. The company differentiates itself with an integrated suite that covers ratings, data, analytics, indices, and ESG solutions across global markets, backed by well-known brands. Its goal is to help clients make informed decisions, manage risk, and drive growth while prioritizing corporate responsibility.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1917

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