Principal Data Scientist

Key Skills

AWS, Dash framework, Data Analytics, Data science techniques, Databricks, Design, Docker, Effective communication skills, Kubernetes-K8s, Machine learning techniques, MLflow, MLOps tools, Python Programming, R Programming, R-Shiny, SQL, Tableau, Writing

Job Description

RESPONSIBILITIES:

• Lead teams creating repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytics solutions and deployable into Production for use by the business
• Provide expert guidance as teams hypothesize and engineer features by using business acumen to find ways to combine disparate internal and external data sources to solve problems
• Drive the thinking across the team and ensure all data science plots/outputs clearly communicate appropriate content and levels of details for business audiences
• Participate in the creation of the analytics roadmap for complex analytics use case development including data science team needs
• Identify opportunities to apply cutting edge approaches, in a well-judged way
• Consider complexity factors such as scalability across models and use cases in guiding the design of the master table
• Scale impact by effectively applying expertise across multi use-cases engagements and identifying synergies
• Proactively share expertise beyond your immediate project
• Share passion for data science with broader enterprise community; identify and develop long-term processes, frameworks, tools, methods, and standards
• Coach, mentor, and collaborate with business partners, analysts, and team members
• Excellent written, verbal communication, presentation, and interpersonal skills
• Ensure data science codebase is well structured, documented and optimized as part of an efficient data pipeline
• Collaborate with team/project leadership to ensure all underlying risks are proactively addressed in overall solution design
• Comfortable operating in ambiguity and in a “start-up” type role where we don’t have all the answers

EXPERIENCE

• Strong understanding of agile methodologies and experience as a Lead Data Scientist on a cross functional agile team preferred
• Proficiency in 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:

• 7+ years of directly related experience in a data science environment with at least 3 years of direct leadership or managerial experience
• 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:

• Proven 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)

LITECH

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