Associate Data Scientist

Jobtailor; Connecticut; On-site; USD 90,000 - 130,000; Full time

Job summary

Jobtailor in Connecticut is seeking a data scientist to develop statistical models, machine learning algorithms, and analytics solutions that support financial objectives and business decisions. You will collaborate with cross-functional teams, review deliverables with partners to calibrate expectations, and identify valuable data sources and analytical techniques for ongoing improvement.

The role requires strong Python, SQL, Unix, and Git skills, plus the ability to articulate insights to

Qualifications

• 2+ years of relevant experience recommended.
• Master's or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, or Computer Science, or progress towards a relevant professional designation.
• Experience in statistical modeling, inference, and building machine learning algorithms in Python.
• Experience in SQL and navigating databases to extract relevant attributes.
• Experience in Unix and Git.
• Experience in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation.
• Exposure to building modeling solutions in cloud-native environments, such as Sagemaker or Vertex AI, a plus.
• Understanding of prompt engineering, retrieval-augmented generation (RAG), agent workflow, and LLM evaluation is a plus.
• Must be authorized to work in the US without company sponsorship
• The company will not support the STEM OPT I-983 Training Plan endorsement for this position

Responsibilities

• Develop statistical models, algorithms, and machine learning techniques to achieve financial objectives and solve business problems
• Review work with business partners and team members to calibrate deliverables against expectations
• Identify and assess the value of new data sources and analytical techniques
• Create and deploy long-term tools to continually evolve the business
• Contribute to strategies achieving targeted business objectives
• Develop knowledge of relevant organizational structures, business processes, and data sources
• Remain current on research techniques and state-of-the-art tools
• Provide economic, qualitative, and statistical support for business decisions
• Participate in the entire model lifecycle while partnering with cross-functional business and technical teams

Skills

Statistical Modeling

Machine Learning Algorithms

Data Analysis

Python Programming

SQL Database Navigation

Unix

Git

Cloud-Native Environments

Modeling Lifecycle

Data Sources Assessment

Education

Master's or Ph.D. in Statistics

Applied Mathematics

Quantitative Economics

Actuarial Science

Data Science

Computer Science

Tools

Sagemaker

Vertex AI

Job description

• Develop statistical models, algorithms, and machine learning techniques to achieve financial objectives and solve business problems
• Review work with business partners and team members to calibrate deliverables against expectations
• Identify and assess the value of new data sources and analytical techniques
• Create and deploy long-term tools to continually evolve the business
• Contribute to strategies achieving targeted business objectives
• Develop knowledge of relevant organizational structures, business processes, and data sources
• Remain current on research techniques and state-of-the-art tools
• Provide economic, qualitative, and statistical support for business decisions
• Participate in the entire model lifecycle while partnering with cross-functional business and technical teams

Requirements

• 2+ years of relevant experience recommended
• Preference for Master's or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or progress towards a relevant professional designation
• Experience in statistical modeling, inference, and building machine learning algorithms in Python
• Experience in SQL and navigating databases to extract relevant attributes
• Experience in Unix and Git
• Experience in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation
• Exposure to building modeling solutions in cloud-native environments, such as Sagemaker or Vertex AI, a plus
• Understanding of prompt engineering, retrieval-augmented generation (RAG), agent workflow, and LLM evaluation is a plus
• Must be authorized to work in the US without company sponsorship
• The company will not support the STEM OPT I-983 Training Plan endorsement for this position

Core Competencies

Demonstrates expertise in statistical modeling, machine learning algorithms, and data analysis to drive financial objectives and business solutions. Proficient in collaborating with cross-functional teams and utilizing advanced analytical techniques to support strategic decision-making.

Highest-signal resume keywords

• Statistical Modeling
• Machine Learning Algorithms
• Python Programming
• SQL Database Navigation
• End-to-End Modeling Lifecycle

ATS Optimization Keywords

Hard Skills

• Statistical Modeling
• Machine Learning
• Data Analysis
• Python Programming
• SQL
• Unix
• Git
• Cloud-Native Environments
• Modeling Lifecycle
• Data Sources Assessment

Soft Skills

• Collaboration
• Communication
• Problem-Solving

Certifications & Qualifications

• Master's or Ph.D. in Statistics
• Applied Mathematics
• Quantitative Economics
• Actuarial Science
• Data Science
• Computer Science

Industry Keywords

• Financial Objectives
• Business Processes
• Analytical Techniques
• Research Techniques
• Model Calibration

Tools & Technologies

• Sagemaker
• Vertex AI