Sr Data Scientist

The Data Scientist / Engineer works with stakeholders to formulate gauge and prioritize business use cases designs experiments develops predictive/prescriptive models on largescale 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 cuttingedge algorithms/models to analyze diverse sources of data to achieve targeted outcomes with a focus on delivering business results including improved end toend 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
  

• 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 endtoend (inception to productization) membercentric 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 cloudbased 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 realreal world inferences for both technical and non technical audiences
  

• Expert level analytical and problemsolving 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