Job Description
The Senior Data Scientist will be responsible for building, training, validating, and deploying advanced machine learning models using structured and unstructured data. The candidate will work closely with cross-functional teams to understand business challenges, develop predictive and analytical solutions, and support the integration of models into production environments.
This role demands strong analytical thinking, hands-on experience in machine learning algorithms, and the ability to build scalable and robust ML pipelines. Exposure to cloud platforms like GCP and basic understanding of data engineering concepts will be an added advantage.
Key Responsibilities
- Design, develop, train, and validate machine learning models for business use cases.
- Build robust and scalable ML pipelines for model training, testing, deployment, and monitoring.
- Apply machine learning techniques including:
- Regression
- Classification
- Unsupervised Learning
- Collaborate with business stakeholders to understand analytical requirements and convert them into scalable data science solutions.
- Provide technical consultation and support to dashboard development and implementation teams for seamless model integration.
- Perform data analysis, feature engineering, model optimization, and performance tuning.
- Ensure model accuracy, reliability, and scalability through proper validation and monitoring techniques.
- Work closely with Data Engineering teams to consume curated datasets and improve model readiness.
- Present analytical findings and recommendations to leadership and business teams.
- Influence marketing and business leadership through data-driven insights and predictive analytics.
- Stay updated with the latest advancements in machine learning, AI, and cloud technologies.
Required Skills
- Strong expertise in Machine Learning model development and deployment.
- Hands-on experience with:
- Regression Models
- Classification Models
- Unsupervised Learning Techniques
- Model Deployment and Productionization
- Strong analytical thinking and problem-solving capabilities.
- Experience in building robust ML pipelines and workflows.
- Proficiency in Python and common ML libraries/frameworks.
- Ability to work collaboratively with cross-functional teams.
- Excellent communication and stakeholder management skills.
