AI/ML Data Scientist

Jobtailor; New York (NY); On-site; USD 65,000 - 90,000; Full time

Job summary

Jobtailor in New York, NY is seeking a data science enthusiast to contribute to customer acquisition, lead scoring, and propensity modeling. You will work with structured data, perform feature engineering, and build ML models using Python and popular libraries.

The role emphasizes hands-on data preparation, model deployment readiness, and collaboration with senior data scientists to translate business problems into analytical solutions. Internship or entry-level experience is acceptable.

Qualifications

• 0–2 years of experience in data science, analytics, or modeling.
• Strong foundation in statistics, ML concepts, and data analysis.
• Proficiency in Python for data analysis and modeling.
• Familiarity with SQL and working with large datasets.
• Basic understanding of supervised ML models used in acquisition or marketing analytics.
• Strong analytical thinking and problem-solving skills.

Responsibilities

• Support development, training, and validation of ML models for acquisition and propensity.
• Perform data preparation and feature engineering on structured datasets.
• Assist in building, testing, and deploying models using Python and ML libraries.
• Develop AI-enabled tools, scripts, and accelerators to improve modeling efficiency.
• Collaborate with senior data scientists to translate business problems into analytical solutions.
• Support model performance monitoring, documentation, and explainability analyses.
• Work with technology and engineering teams to ensure models can be operationalized and scaled.
• Hands-on exposure to AI-driven model development, automation, and analytical tool building.
• Contribute to internal AI utilities, notebooks, APIs, or model frameworks that enhance productivity.
• Work in modern analytics environments using cloud platforms, notebooks, and version control (e.g., Git).

Skills

Python

SQL

Statistics

Machine Learning

Analytical Thinking

Problem Solving

Tools

scikit-learn

XGBoost

LightGBM

Job description

Responsibilities

• Support the development, training, and validation of machine learning models focused on customer acquisition, lead scoring, response modeling, and propensity modeling.
• Work with structured datasets to perform data preparation, feature engineering, and exploratory analysis.
• Assist in building, testing, and deploying models using Python and ML libraries (e.g., scikit‑learn, XGBoost, LightGBM, etc.).
• Contribute to the development of AI‑enabled tools, reusable scripts, and modeling accelerators to improve modeling efficiency and consistency.
• Collaborate with senior data scientists to translate business problems into analytical solutions.
• Support model performance monitoring, documentation, and basic explainability analysis.
• Partner with technology and engineering teams to ensure models can be operationalized and scaled.
• Hands‑on exposure to AI‑driven model development, automation, and analytical tool building.
• Opportunity to contribute to internal AI utilities, notebooks, APIs, or model frameworks that enhance productivity.
• Work in modern analytics environments using cloud platforms, notebooks, and version control (e.g., Git).

Requirements

• 0–2 years of experience (or relevant internships/projects) in data science, analytics, or modeling.
• Strong foundation in statistics, machine learning concepts, and data analysis.
• Proficiency in Python for data analysis and modeling.
• Familiarity with SQL and working with large datasets.
• Basic understanding of supervised ML models used in acquisition or marketing analytics.
• Strong analytical thinking and problem‑solving skills.