Description

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

This role is on-site.

Responsibilities

• Formulate and prioritize business use cases through stakeholder consulting.
• Generate, process, and verify data integrity for analysis pipelines.
• Implement and validate algorithms to improve customer experience and financial metrics.
• Collaborate with ML and DevOps teams to operationalize enterprise solutions.
• Provide technical guidance and mentorship through code and design reviews.

Required Skills

• 5+ years of professional experience in data science within financial services.
• 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 (AWS, Azure, Google, MLaaS, or AIaaS).
• Demonstrated experience with containers (Docker, Kubernetes) and Git.
• Expertise in experimental design, A/B testing, and multivariate testing.

Preferred Skills

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

Education

• Master's degree in Mathematics, Statistics, Data Science, Econometrics, or a relevant field.
• Data Science related certifications.

Key Skills

Education

Any Graduate