Data Scientist – Predictive & Intelligent Modeling

About the role

We are seeking an experienced Data Scientist to design, develop, and productionize predictive and intelligent models across machine learning, deep learning, NLP, and computer vision. The role emphasizes rigorous statistical methodology, model reliability, and translating analytical insights into tangible business outcomes.

Key responsibilities

• Own end‑to‑end model development, experimentation, evaluation, and production readiness.
• Build forecasting, optimization, recommendation, decision‑science, and machine‑learning models.
• Perform feature engineering, exploratory data analysis, and statistical analysis to uncover meaningful patterns.
• Design and implement rigorous model evaluation, validation, and testing frameworks.
• Validate model performance, fairness, and bias before deployment.
• Manage experiment tracking, datasets, and model reproducibility using tools such as MLflow or Weights & Biases.
• Present model results, trade‑offs, and uncertainty to business stakeholders.
• Collaborate with ML Engineers and Architects to productionize models.
• Lead complex decision‑intelligence engagements when required.
• Mentor junior Data Scientists and ML Engineers.

Required profile

• 5+ years of applied Data Science experience with a proven record of shipping production models.
• Strong expertise in classical/statistical machine learning, forecasting, optimization, and deep learning.
• Experience with NLP, computer vision, graph‑based features, or knowledge graphs is a plus.
• Excellent communication skills and ability to explain technical concepts and model trade‑offs to business stakeholders.
• Ability to defend modeling decisions and work closely with engineering and architecture teams.

Required skills

• Python programming
• SQL
• scikit‑learn
• PyTorch or TensorFlow
• MLflow or Weights & Biases
• Hypothesis testing, confidence intervals, and causal inference
• Fairness and bias evaluation
• Explainability tools such as SHAP and LIME