The Role :
As a Lead Data Scientist, you'll be responsible for end-to-end ownership of critical data science products, from conceptualization and model development to deployment in a production environment.
You will lead projects focused on areas like customer churn prediction, recommendation systems, and dynamic pricing optimization, directly impacting key business metrics.
What You'll Do :
- Model Development : Design, train, and evaluate highly accurate machine learning models (Classification, Regression, NLP, Deep Learning) to solve complex business problems.
- MLOps & Deployment : Work with DevOps / MLOps teams to implement and manage CI / CD pipelines for ML models, ensuring reliable and scalable production deployment.
- Feature Engineering & Data Cleaning : Master complex, large-scale datasets, focusing on advanced feature engineering and data transformation.
- Stakeholder Communication : Translate complex analytical findings and model results into clear, actionable insights and compelling visualisations for non-technical stakeholders.
- Research & Innovation : Stay abreast of the latest advancements in AI / ML research and propose new methodologies or technologies to maintain a competitive edge.
Required Skills & Qualifications :
6+ years of experience in Data Science, with a focus on building and deploying ML models in a commercial setting.Expert proficiency in Python (Pandas, NumPy, Scikit-learn) and ML frameworks (TensorFlow / PyTorch).Exceptional skills in SQL for data extraction and manipulation.Proven experience with MLOps tools (e.g., MLflow, Kubeflow) and cloud platforms (AWS SageMaker, GCP AI Platform).Deep statistical knowledge and experience with A / B testing and experimental design.Master's or PhD in a quantitative field (Computer Science, Statistics, Mathematics)(ref : hirist.tech)