Data Scientist II

Role Overview

• Participate in extending product capabilities through development and deployment of analytical systems leveraging data mining, generative AI, and ML techniques.
• Interact with 3rd parties to evaluate integration feasibility and licensing of technologies and analytic components
• Design, prototyping, and implementation of new data-centric solutions
• Effectively communicate and collaborate with local teams, international teams, and 3rd parties
• Contribute to build versus buy decisions
• Work closely with members of Product Management, New Product Development, Quality Assurance, and end users as may be necessary to bring solutions to life
• Self-starter that can take minimal direction and deliver results
• Curious problem solver

Requirements

• BS or MS in an appropriate technology field (Computer Science, Statistics, Applied Math, etc.)
• 2+ years of experience in modern advanced analytical tools and programming languages, including Python with scikit-learn
• Some experience with exploratory data analysis
• Some experience with ETL operations sourcing data from SQL, REST APIs, and flat files
• Basic experience with data visualization technologies, such as Power BI, Tableau, matplotlib, Excel, etc.
• 2+ years of experience in traditional programming languages such as Python, JavaScript, TypeScript, C++, or C#
• Comfortable in Windows and Linux environments
• Some exposure to building generative AI applications leveraging embeddings, LLMs, VLMs, vector databases, data source APIs, and agentic patterns/frameworks
• Basic understanding of various deployment topologies including on-premises, hybrid, and cloud for production generative AI applications
• Basic understanding of building predictive and decision-making AI applications.
• Some exposure to using cloud services from AWS, Azure, or GCP to develop solutions.
• Awareness of computer vision and image/video analysis, including object detection, recognition, tracking, and identification
• Some exposure with application of data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural networks, SVMs, anomaly detection, recommender systems, pattern discovery, and text mining
• Problem Solving: Ability to solve problems using analytical thinking, reconciling viewpoints, and evaluating technologies.
• Communication: Demonstrates effective verbal and written communication skills when explaining complex technical issues to both technical and non-technical audiences
• Continuous learning mindset

Tech Stack

• AWS
• Azure
• Cloud
• ETL
• Google Cloud Platform
• JavaScript
• Linux
• Python
• Scikit-Learn
• SQL
• Tableau
• TypeScript

Benefits

• employer subsidized Medical, Dental, Vision, and Life Insurance
• Short-Term and Long-Term Disability
• 401(k) match
• Flexible Spending Accounts
• Health Savings Accounts
• EAP
• Educational Assistance
• Parental Leave
• Paid Time Off (for vacation, personal business, sick time, and parental leave)
• 12 Paid Holidays