Data Science Engineer
S&P Global Ratings is looking for an experienced Data Science Engineer to join Data Engineering team within Chief Data Office, a team of data and technology professionals who define and execute the strategic data roadmap for S&P Global Ratings. The successful candidate will participate in the design and build of S&P Ratings cloud based analytics platform to help develop and deploy advanced analytics/machine learning solutions.
You will be an expert contributor and part of the Rating Organization's Data Services Team. This team, who has a broad and expert knowledge on Ratings organization's critical data domains, technology stacks and architectural patterns, fosters knowledge sharing and collaboration that results in a unified strategy. All Data Services team members provide leadership, innovation, timely delivery, and the ability to articulate business value. Be a part of a unique opportunity to build and evolve S&P Ratings next gen analytics platform.
Our Hiring Manager Says
If you are an individual that brings demonstrated experience of delivering big data projects as a data science engineer,, this is an excellent opportunity. I am looking for someone with sound technical knowledge, can be hands-on, worked on transformational initiatives, and can drive results.
• Design and develop efficient and scalable data pipelines between enterprise systems and analytics platform
• Work closely with Data Science team and participate in development and deployment of machine learning models and feature engineering pipelines
• Provide technical expertise in the areas of design and implementation of Ratings Integrated Data Facility with modern AWS cloud technologies such as S3, Redshift, EMR, Hive, Presto and Spark
• Build and maintain a data environment for speed, accuracy, consistency and 'up' time
• Support analytics by building a world-class data lake environment that empowers analysts to determine insights into revenue and power products across the organization
• Work with the machine learning engineering team to build a data eco system that supports AI products at scale
• Ensure data governance principles adopted, data quality checks and data lineage implemented in each hop of the data
• Partner with the chief data office, enterprise architecture organization to ensure best use of standards for the key data domains and use cases
• Be in tune with emerging trends Big data and cloud technologies and participate in evaluation of new technologies
• Ensure compliance through the adoption of enterprise standards and promotion of best practice / guiding principles aligned with organization standards
Experience & Qualifications:
• BS or MS degree in Computer Science or Information Technology
• 8+ years of experience as data engineer at an innovative organization
• 4+ years of hands-on experience in implementing data lake systems using AWS cloud technologies such as S3, Redshift, EMR, Hive, Presto and Spark
• Expert managing AWS services (EC2, S3, Route 53, ELB, VPC, cloudwatch, Lambda) in a multi account production environment
• Experience With Machine Learning Frameworks, such as TensorFlow , PyTorch, H2O, scikit-learn, Theano, Caffe or Spark MLib is an added advantage
• Exposure to R, SparkR, SparklyR or Other R packages is a plus
• Experience in constructing fast data staging layers to feed machine learning algorithms
• Experience in building data APIs to consume analytic model output
• Familiarity with machine learning model training and deployment process is a plus
• Experience with development frameworks as well as data and integration technologies such as Python, Scala or Informatica
• Expert knowledge of Agile approaches to software development and able to put key Agile principles into practice to deliver solutions incrementally.
• Monitors industry trends and directions; develops and presents substantive technical recommendations to senior management
• Excellent analytical thinking, interpersonal, oral and written communication skills with strong ability to influence both IT and business partners
• Ability to prioritize and manage work to critical project timelines in a fast-paced environment
• Financial services industry experience