Description

You will design experiments and develop predictive and prescriptive models on large-scale structured and unstructured datasets to drive business value in the financial services sector.

Responsibilities

• Formulate, gauge, and prioritize business use cases through consulting sessions with stakeholders.
• Generate, process, cleanse, and verify the integrity of data and analysis pipelines.
• Implement and validate algorithms to improve customer experience and financial metrics.
• Collaborate with Machine Learning and IT DevOps teams to operationalize and productize enterprise solutions.
• Provide technical guidance and mentorship to peers through code and design reviews.

Required Skills

• 5+ years of professional experience in a data science role implementing end-to-end solutions in the financial services industry.
• Expert knowledge of NLP, LLMs, and predictive/prescriptive analytics.
• Deep understanding of machine learning techniques including clustering, classification, regression, neural nets, and deep learning.
• Proficiency in Python, PySpark, R, and TensorFlow.
• Expert knowledge of SQL and databases.
• Professional experience with Kafka, Kinesis, Spark, and Snowpark.
• Experience with cloud technologies including AWS, Azure, Google, MLaaS, or AIaaS.
• Demonstrated experience with containers (Docker, Kubernetes) and Git.
• Expertise in experimental design, A/B testing, and multivariate testing.
• Master's degree in Mathematics, Statistics, Data Science, Econometrics, or a relevant field.
• Required Data Science related certifications.

Preferred Skills

• Experience with Snowflake and Dataiku Data Science Studio.
• Experience with Tableau for data visualization.

Key Skills

Education

Any Graduate