The Opportunity :

We are seeking a seasoned Data Scientist to lead the end-to-end development, deployment, and monitoring of Machine Learning models.

You will be responsible for defining the problem, exploring data, developing robust models, and working with ML Engineers to see your solutions deployed at scale.

Key Responsibilities :

- Work with business stakeholders to define and frame data science problems into clear objectives and deliverables (e.g., churn prediction, recommendation engines, anomaly detection).

- Design, develop, and validate scalable Machine Learning and Deep Learning models using rigorous statistical methods.

- Perform extensive data exploration, feature engineering, and data cleaning on large, complex datasets.

- Establish MLOps best practices for model versioning, testing, deployment, and monitoring in production.

- Present complex findings and model performance to both technical and non-technical audiences.

- Mentor junior team members and stay current with the latest research and industry trends.

Required Technical Skills :

- Expert proficiency in Python (Pandas, NumPy, Scikit-learn, Matplotlib).

- Deep practical experience with at least one major Deep Learning framework: TensorFlow or PyTorch.

- Strong SQL skills and experience with big data processing (e.g., Apache Spark, Databricks).

- Practical experience with tools for productionizing ML models (MLflow, AWS SageMaker, Kubeflow).

- Proven track record in developing and deploying models in [mention domain, e.g., NLP, Computer Vision, Time Series Forecasting].

- Masters or Ph.D. in Computer Science, Statistics, or a related quantitative field.

Bonus Points :

- Experience with generative AI models (e.g., LLMs) and fine-tuning techniques