Sr Data Scientist

Job Description
The Data Scientist / Engineer works with stakeholders to formulate, gauge and prioritize business use cases, designs experiments, develops predictive/prescriptive models on large-scale datasets (structured and unstructured) to address them, and uses statistics, complex analyses and machine learning models to drive member value and business success. In addition, the Data Scientist / Engineer cooperates with the Machine Learning and IT DevOps teams to ensure operationalization and productization of solutions generated at an Enterprise level.

Generate, process, cleanse, and verify the integrity of data and the data pipelines used for analysis

Implement and validate cutting-edge algorithms/models to analyze diverse sources of data to achieve targeted outcomes with a focus on delivering business results including improved end- to-end customer experience and financial metrics

Provide meaningful insights through advanced analytics models and solutions targeted to respond to critical business issues and accelerate stakeholder growth and success

Participate in consulting sessions with stakeholders regarding generation, gauging and prioritization of business use cases using advanced analytics. Establish and present metrics on the progress and success of advanced analytics initiatives

Deliver informative and effective findings, results and recommendations from statistical analysis to stakeholders

Recommend ongoing improvements to methods and algorithms currently in production

Act as a subject matter expert in providing technical guidance and mentorship to peer team

members on analytics and analysis best practices, solution design as well as lead code/design reviews

Requirements
Minimum Education: Master’s degree in Mathematics, Statistics, Data Science, Econometrics, or relevant fields

Minimum 5 years’ professional experience in a data science role, working with large amounts of data, and implementing end-to-end (inception to productization) member-centric solutions in the financial services industry

Expert knowledge and experience in NLP, LLMs, predictive and prescriptive analytics approaches

Deep understanding of machine learning (ML) techniques including but not exhausted to clustering, classification, regression, decision trees, neural nets, support vector machines, genetic algorithms, anomaly detection, association rules, sequential pattern discovery and deep learning

Demonstrated experience with common business intelligence and data visualization tools (Tableau preferred)

Demonstrated experience with cloud-based Data Science platforms (Dataiku Data Science Studio preferred)

Professional experience with Kafka, Kinesis, Spark, Snowpark

Professional experience with cloud technologies (AWS, Azure, Google, MLaaS, AiaaS)

Proficiency in the use of scripting languages and ML platforms (Python, PySpark, R, TensorFlow)

Expert knowledge of SQL and databases. Experience with Snowflake preferred

Demonstrated experience with containers (Kubernetes, Docker), Git

Demonstrated experience in experimental design, A/B and multivariate testing

Expert command of the English language, persuasive written and verbal communication and an ability to effectively tell stories with data

Exemplary communication skills; oral and written, with ability to translate complex statistical and quantitative analysis into simple real-real world inferences for both technical and non- technical audiences

Expert level analytical and problem-solving skills with attention to detail

Ability to translate business objectives into actionable analyses

Demonstrated effective time management skills and the ability to work independently or in a collaborative team environment

Advanced knowledge of Microsoft Office Suite

Certification/License: Data Science related certifications required