Data Scientist

We are seeking a Data Scientist with over six years of hands-on experience to lead the end-to-end design, development, and deployment of machine learning and statistical models. You will collaborate with cross-functional teams to translate business needs into data science problems, and build production-grade models using Python, SQL, and PySpark. This role requires a deep understanding of ML/DL algorithms and model development workflows, with a preference for candidates who have a master's degree and experience with MLOps tools.

Roles & Responsibilities:

• Model Development & Deployment: Lead the end-to-end design, development, and deployment of machine learning/statistical models for real-world business applications.
• Cross-functional Collaboration: Collaborate with Product, Engineering, and Business teams to translate their needs into data science problems.
• Technology Implementation: Build and productionize models using Python, SQL, and PySpark on large-scale datasets.
• Algorithm Application: Apply deep learning and advanced statistical techniques for tasks such as classification, regression, recommendation, and personalization.
• Model Lifecycle Management: Perform data wrangling, feature engineering, model tuning, and evaluation. Monitor and manage the ML model lifecycle using tools like MLflow and Airflow.
• Communication & Innovation: Communicate technical insights and findings effectively to both technical and non-technical stakeholders. Stay updated on the latest trends in ML and AI.

Skills Required:

• 6+ years of hands-on experience in data science.
• Strong Python skills, including libraries such as NumPy, pandas, scikit-learn, and TensorFlow/PyTorch.
• Proficiency in SQL and experience with PySpark or distributed data processing.
• Deep understanding of ML/DL algorithms, model development workflows, and statistical modeling.
• Proven ability to deploy and manage production-grade models at scale.
• Experience with MLOps tools (MLflow, Airflow, Docker, Kubernetes) is a plus.
• Familiarity with deploying ML APIs using FastAPI or similar frameworks is a plus.

QUALIFICATION:

• Masters degree in Computer Science, AI, or a related technical field is preferred.