The Financial Services Data Scientist will join a diverse and experienced team of data scientists, data engineers, financial engineers, and software developers to develop innovative solutions to challenging analytical, data-driven problems for the world’s leading financial institutions.
- As part of the Analytics and Data Science team, the Data Scientist will be responsible for translating client and market needs into commercial solutions and contribute to the development of Accelerators demonstrating Synechron’s expertise in technology, consulting, and digital solutions.
- The Data Scientist will develop AI and ML models using a variety of languages including Python, PySpark, R, and Scala.
- The Data Scientist will work as part of a team on everything from data ingestion and transformation to model development and management to data visualization.
- The ideal candidate will have significant (5+ years) model development experience in the financial services industry, including specific experience developing, testing, and validating credit risk models.
- The ideal candidate will have 5+ years of experience developing credit risk models in SAS, Python, and R.
- Experience developing, validating, and implementing credit risk models for large banks in the wholesale and credit loan space is highly desired.
- The ideal candidate should also be familiar with developing models executed in distributed data platforms including Hadoop (HDFS) and MapR as well as using frameworks such as Spark.
- The Data Scientist will initially work on a large scale end-to-end model development, validation, and execution platform for a Tier 1 global bank and later work on the development of the firm’s AI/ML Accelerators as well as client-specific engagements.
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