About the job
Join a team that transforms how we serve millions of customers through AI innovation and build next-generation solutions that reinvent CRMs and reimagine client and employee interactions. As a Data Science Senior Associate, with the Branch Channel Generative AI Team, you will develop solutions and experiment with state of the art models, at the same time, contributing to innovative projects and drive the future of field AI Technologies.
Responsibilities
Design controlled experiments to test and validate hypotheses.
Translate business needs into data models supporting long-term solutions.
Work with a wide range of proprietary, industry-standard, and open-source data stores and tools to assemble, organize, and analyze data.
Work closely with data owners and data curation teams to build/or use the relevant data
Convert data into actionable insights.
Utilize data visualization tools to effectively communicate findings.
Leverage statistical and mathematical techniques and algorithms to solve complex business problems.
Qualifications
Minimum
MS and/or PhD in Statistics, Computer Science, Machine Learning, or a related field, with at least 3 years of model experimentation and at least 3 years’ experience in applying data science to solve business problems.
Strong knowledge of various business data and be comfortable to work with data owners and data curation teams to build/or use the relevant data.
Strong Python and SQL background with at least 3 year's experience in those areas.
Excellent communication and stakeholder management; comfort working across the quad team and understand the required data for a use case.
Be able to define success metrics, run A/B tests independently, capture user feedbacks, and analyze the results and provide insights.
Good knowledge of various ML models
Knowledge of model safety, bias, and privacy techniques; experience with model risk management and governance.
Preferred
Experience with PySpark or distributed compute
Software development experience is a plus
Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
Experience with building and deploying models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.