Consider implementation constraints, both business and technical, and defines approach across increasingly complex / large analytics use cases
Autonomously define the master table for increasingly complex engagements with a good understanding of all trade-offs in model building
Contribute to feature validation
Independently deliver one or multiple workstreams over the full duration of a project
Have an excellent understanding of leading-edge methodologies with emerging spikes in one or more methodologies (e.g., deep learning) or domains. Can apply these rigorously to a range of problems
Guide junior colleagues in the application of analytics approaches
Create series of outputs / plots that build upon each other to guide problem solving with business teams. Suggests outputs across all workstreams
Write production code optimized for efficiency and memory
Conduct code reviews with junior colleagues
Lead overall model validation / QA approach across the engagement
Excellent understanding of risks and how to mitigate
Raise potential ethical issues related to analytics to leadership
EXPERIENCE :
Strong understanding of agile methodologies and experience as a Sr Data Scientist on a cross functional agile team preferred
Proficiency applying data science techniques on large scale data sets. E.g., machine learning to solve clustering, classification, regression, anomaly detection problem statements; and optimization or simulation techniques to solve prescriptive problems
Proven ability to derive new insights by merging and transforming internal and external data sets in business contexts
Experience with supporting deployment, monitoring, maintenance, and enhancement of models preferred
Experience with cloud database technologies (e.g., AWS) and developing solutions on cloud computing services and infrastructure in the data and analytics space
QUALIFICATIONS REQUIRED :
4+ years of directly related experience in a data science environment.
Bachelor’s degree required, MS or PhD preferred in the field of data science, computer science, engineering, mathematics, statistics, or related fields
Python or R required; SQL preferred
PREFERRED QUALIFICATIONS : Preference will be given to candidates who have the following :
Demonstrated ability to efficiently learn and solve new business domains and problems
Nice to have experience with popular open-source or commercial optimization libraries (e.g. Gurobi, CPLEX)
Knowledge with dashboarding tools (e.g., Dash, Shiny, Tableau)
Nice to have knowledge with MLOps infrastructure (e.g., Databricks, MLflow) and containerization and managing production pipelines and microservices (e.g., Docker, Kubernetes)
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