Data Scientist - Machine Learning (3-6 yrs)

Job Description :

We are looking for a highly skilled Data Science Engineer with 3-6 years of experience to design, build, and deploy machine learning models and advanced data solutions. The ideal candidate will be responsible for extracting insights from large datasets, developing data pipelines, and collaborating with cross-functional teams to apply data-driven approaches to business challenges. A strong foundation in data science, machine learning, and data engineering is essential for success in this role.

Key Responsibilities :

1. Model Development and Optimization :

- Build, train, and optimize machine learning models for classification, regression, clustering, and recommendation tasks.

- Perform data preprocessing, feature engineering, and selection to improve model accuracy and performance.

- Implement machine learning algorithms using frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.

2. Data Pipeline and Infrastructure Development :

- Develop and maintain scalable data pipelines for model training, testing, and deployment.

- Collaborate with data engineers to ensure smooth integration of models into production environments.

- Ensure data infrastructure is optimized for handling large datasets and real-time data streams.

3. Data Analysis and Visualization :

- Conduct exploratory data analysis (EDA) to discover trends, patterns, and insight in large datasets.

- Use data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) to present data-driven insights to non-technical stakeholders.

- Assist in generating regular reports and dashboards to support business decisions.

4. Model Deployment and Monitoring :

- Deploy machine learning models into production, ensuring performance, scalability, and reliability.

- Monitor the performance of models over time, retraining and optimizing as needed.

- Implement best practices for model validation, A/B testing, and model retraining processes.

5. Collaboration with Cross-Functional Teams :

- Work closely with software engineers, product managers, and business analysts to ensure that data science solutions meet business requirements.

- Collaborate with the IT team to integrate machine learning models into company systems and applications.

- Provide data science expertise and support to other teams for developing data-driven solutions.

6. Research and Innovation :

- Stay up-to-date with the latest developments in data science, machine learning, and AI.

- Explore new tools, techniques, and approaches to enhance data science workflows and processes.

- Implement innovative solutions for improving model performance, data handling, and deployment techniques.