Data Scientist II

About the role

Advances broad capabilities in using and deploying cutting-edge data science and machine learning tools and methods in projects, platforms, and products. Anchors current best practices by supporting the design and build of reusable data science assets. Works to stay on the bleeding edge by understanding the latest and most sophisticated methods and tools for tackling extremely large-scale and complex problems.

Responsibilities

• Applies descriptive, diagnostic, predictive, prescriptive, and ensemble modeling, statistical techniques, machine learning methods, and AI-driven approaches to analyze complex business situations and support decision-making.
• Provides recommendations to moderately complex issues through the application of data science, machine learning, Generative AI, and data engineering practices, leveraging data-driven insights to support business objectives.
• Works in tandem with peer data scientists, engineers, and business stakeholders to develop, test, and deploy end-to-end analytical, machine learning, and AI solutions.
• Assists in the development, evaluation, and deployment of machine learning, Generative AI, and LLM-based solutions, including experimentation, model validation, and performance monitoring.

Requirements

• Minimum Education: Master’s degree (or equivalent) in Computer Science, Operations Research, Statistics, Applied Mathematics, or a related quantitative field.
• Minimum Experience: At least two (2) years of professional experience applying data science (e.g., machine learning, artificial intelligence, statistical analysis), operations research (e.g., optimization, algorithms, mathematical modeling), and data analytics to reduce costs, enhance profitability, and improve customer experience.

Qualifications

• Preferred Experience: At least two (2) years of professional experience applying data science (e.g., machine learning, artificial intelligence, statistical analysis, Generative AI), operations research (e.g., optimization, algorithms, mathematical modeling), and data analytics to improve customer experience, reduce costs, enhance profitability, and solve business problems.
• Experience developing or supporting end-to-end analytics and machine learning solutions is preferred.

Skills

• Descriptive, Diagnostic, Predictive, Prescriptive, and Ensemble Modeling
• Statistical Techniques
• Machine Learning Methods
• AI-Driven Approaches
• Data Engineering Practices

Benefits

• Remote Work Eligibility: Yes, this position is eligible for remote work and may be located anywhere within the United States excluding AK, HI and U.S. territories.
• Compensation Range: $6,168.90/mo - $13,571.58/mo (USA), $6,168.90/mo - $13,006.09/mo (CO), $6,511.62/mo - $10,898.39/mo (CA), $6,511.62/mo - $10,418.59/mo (NJ), $6,511.62/mo - $10,744.16/mo (OH & VT), $6,511.62/mo - $12,440.61/mo (MN), $6,511.62/mo - $13,006.09/mo (IL & NV), $6,511.62/mo - $13,571.58/mo (MD, NY & WA), $6,854.33/mo - $13,571.58/mo (MA), $7,539.76/mo - $12,440.61/mo (RI), $7,539.76/mo - $13,006.09/mo (CT), $7,882.48/mo - $13,006.09/mo (DC & HI), $7,882.48/mo - $13,571.58/mo (NYC).

Pay

• Pay Transparency: Pay is determined based on location and experience.

Schedule

• Remote Work Eligibility: Yes, this position is eligible for remote work and may be located anywhere within the United States excluding AK, HI and U.S. territories.