AI / ML Data Scientist

Role Overview
We are looking for a Junior Modeling professional to support the development and deployment of machine learning models for customer acquisition. This role is ideal for candidates with 0–2 years of experience who are excited about applying data science, AI, and coding to solve real‑world business problems and scale analytics solutions.

Key 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.
•    AI & Technology Exposure
•    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).
•    Learn best practices in coding standards, model lifecycle management, and responsible AI.

Required Qualifications
•    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.