Senior Data Scientist

Jobtailor; Town of Florida (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor in New York is seeking an experienced data scientist to independently design and implement statistical and machine-learning solutions for complex business problems. You will own end-to-end analytical workstreams, collaborating with data scientists, data engineers, and business partners to deliver predictive models for pricing, product development, and growth.

The role requires strong Python and SQL skills, 4+ years of ML experience, plus the ability to communicate findings to technical

Qualifications

• Bachelor’s degree in Mathematics, Statistics, Engineering, or another STEM field with at least 8 years of relevant experience, or a graduate degree in a STEM field with at least 6 years of relevant experience in the insurance industry, data science/analytics, or a related environment
• At least 4 years of firsthand experience with statistical modeling and AI/ML platforms
• Demonstrated experience independently developing and delivering statistical or machine-learning solutions
• Strong proficiency in Python, including pandas, NumPy, scikit-learn, SciPy, and visualization libraries
• Strong proficiency in SQL for large and complex datasets
• Strong understanding of statistical modeling and machine learning concepts
• Hands-on experience with statistical and machine learning techniques, including generalized linear models, regularized regression, tree-based models, ensemble methods, clustering, or neural networks
• Ability to develop readable, maintainable, modular, and well-documented Python code and reusable analytical workflows
• Experience working with large and complex structured datasets and common data formats
• Ability to independently develop analytical approaches for complex or ambiguous business problems
• Ability to translate technical methodologies, results, and recommendations for technical and business audiences
• Ability to independently manage significant analytical workstreams while collaborating with data scientists, data engineers, and business partners
• Experience participating in model reviews, code reviews, and technical discussions
• Sponsorship is not accepted for this opportunity
• PhD in a STEM field preferred, with at least 4 years of relevant industry experience
• Prior experience in insurance, financial services, pricing, risk modeling, or a related analytical business environment preferred
• Experience applying predictive modeling techniques preferred
• Experience with Git, GitLab, or other version control tools preferred
• Experience with AWS, Azure, Databricks, or similar cloud platforms preferred
• Familiarity with MLOps practices preferred
• Experience developing reusable or modular analytical frameworks preferred
• Experience providing technical guidance or mentoring preferred

Responsibilities

• Independently design, develop, validate, and implement statistical and machine-learning solutions for complex business problems
• Own analytical and modeling workstreams from problem definition through delivery and performance monitoring
• Develop predictive modeling and analytical solutions supporting pricing segmentation, product development, and profitable growth
• Collaborate with data scientists, data engineers, and business partners on scalable analytical solutions
• Develop reusable, well-documented analytical workflows using modern data science and cloud technologies
• Manage priorities, deliverables, and timelines for assigned projects
• Communicate progress, risks, results, and recommendations to stakeholders
• Participate in model and code reviews and recommend methodological or implementation enhancements
• Provide technical guidance to less experienced team members
• Contribute to data science best practices

Skills

Statistical Modeling

Machine Learning Techniques

Python

SQL

Generalized Linear Models

Regularized Regression

Tree-Based Models

Ensemble Methods

Clustering

Neural Networks

Communication

Problem Solving

Project Management

Collaboration

Technical Guidance

Education

Bachelor's degree in Mathematics, Statistics, Engineering, or another STEM field

Graduate degree (Master's/PhD) in STEM with 6+ years of experience

Tools

AWS

Azure

Databricks

Git

GitLab

Job description

• Independently design, develop, validate, and implement statistical and machine-learning solutions for complex business problems
• Own analytical and modeling workstreams from problem definition through delivery and performance monitoring
• Develop predictive modeling and analytical solutions supporting pricing segmentation, product development, and profitable growth
• Collaborate with data scientists, data engineers, and business partners on scalable analytical solutions
• Develop reusable, well-documented analytical workflows using modern data science and cloud technologies
• Manage priorities, deliverables, and timelines for assigned projects
• Communicate progress, risks, results, and recommendations to stakeholders
• Participate in model and code reviews and recommend methodological or implementation enhancements
• Provide technical guidance to less experienced team members
• Contribute to data science best practices

Requirements

• Bachelor's degree in Mathematics, Statistics, Engineering, or another STEM field with at least 8 years of relevant experience, or a graduate degree in a STEM field with at least 6 years of relevant experience in the insurance industry, data science/analytics, or a related environment
• At least 4 years of firsthand experience with statistical modeling and AI/ML platforms
• Demonstrated experience independently developing and delivering statistical or machine-learning solutions
• Strong proficiency in Python, including pandas, NumPy, scikit-learn, SciPy, and visualization libraries
• Strong proficiency in SQL for large and complex datasets
• Strong understanding of statistical modeling and machine learning concepts
• Hands-on experience with statistical and machine learning techniques, including generalized linear models, regularized regression, tree-based models, ensemble methods, clustering, or neural networks
• Ability to develop readable, maintainable, modular, and well-documented Python code and reusable analytical workflows
• Experience working with large and complex structured datasets and common data formats
• Ability to independently develop analytical approaches for complex or ambiguous business problems
• Ability to translate technical methodologies, results, and recommendations for technical and business audiences
• Ability to independently manage significant analytical workstreams while collaborating with data scientists, data engineers, and business partners
• Experience participating in model reviews, code reviews, and technical discussions
• Sponsorship is not accepted for this opportunity
• PhD in a STEM field preferred, with at least 4 years of relevant industry experience
• Prior experience in insurance, financial services, pricing, risk modeling, or a related analytical business environment preferred
• Experience applying predictive modeling techniques preferred
• Experience with Git, GitLab, or other version control tools preferred
• Experience with AWS, Azure, Databricks, or similar cloud platforms preferred
• Familiarity with MLOps practices preferred
• Experience developing reusable or modular analytical frameworks preferred
• Experience providing technical guidance or mentoring preferred

Core Competencies

Demonstrates expertise in developing and implementing statistical and machine-learning solutions, with strong proficiency in Python and SQL for data analysis. Capable of managing complex analytical workstreams while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

• Statistical Modeling
• Machine Learning Solutions
• Python Proficiency
• SQL for Data Analysis
• Analytical Workflow Development

ATS Optimization Keywords

Hard Skills

• Statistical Modeling
• Machine Learning Techniques
• Python
• SQL
• Generalized Linear Models
• Regularized Regression
• Tree-Based Models
• Ensemble Methods
• Clustering
• Neural Networks

Soft Skills

• Communication
• Collaboration
• Technical Guidance
• Problem Solving
• Project Management

Industry Keywords

• Insurance Industry
• Data Science
• Predictive Modeling
• Risk Modeling
• Financial Services

Tools & Technologies

• AWS
• Azure
• Databricks
• Git
• GitLab