Data Scientist – ML, Deep Learning, NLP & Computer Vision

About the role

We are seeking an experienced Data Scientist to design, develop, and productionize advanced predictive and intelligent models across machine learning, deep learning, natural language processing, and computer vision. The role bridges data science and business, turning analytical insights into measurable 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 rigorous evaluation, validation, and testing frameworks for models.
• Validate model performance, fairness, and bias before deployment.
• Manage experiment tracking, datasets, and 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 production model‑shipping.
• Strong expertise in classical/statistical ML, forecasting, optimization, and deep learning.
• Experience with NLP, computer vision, graph‑based features, or knowledge graphs is a plus.
• Excellent communication skills to explain technical concepts and model trade‑offs to business audiences.
• Ability to defend modeling decisions and work closely with engineering and architecture teams.

Required skills

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