Senior Data Scientist - Data Science and Analytics (Gen-AI)

What are we looking for?

A highly experienced Senior Data Scientist with 7-9 years of experience in Gen-AI to join the Data Labs team.

What does the job entail?

Developing and deploying AI and machine learning models to drive business growth and innovation.

Collaborating with cross-functional teams to integrate AI solutions into existing systems and processes.

Designing and implementing data pipelines and architectures to support AI model development and deployment.

Staying up-to-date with the latest advancements in AI and machine learning to continuously improve and refine models.

Providing data-driven insights and recommendations to inform business decisions.

Mentoring and guiding junior data scientists and engineers to help them grow in their careers.

Developing and maintaining high-quality, efficient, and scalable AI models and algorithms.

Collaborating with stakeholders to identify business needs and develop solutions to meet those needs.

Conducting experiments and analyzing results to optimize AI model performance.

Ensuring data quality, integrity, and security throughout the AI development process.

Working with large datasets and developing data visualizations to communicate insights to non-technical stakeholders.

Designing and implementing A/B testing and experimentation frameworks to measure the impact of AI-driven decisions.

Work Experience

7 - 9 Years

Essential Qualification

Graduate/ Post Graduate

Preferred Skills

Strong expertise in machine learning, deep learning, and natural language processing.

Proficiency in programming languages such as Python, R, and SQL.

Experience with popular deep learning frameworks like TensorFlow and PyTorch.

Knowledge of cloud-based platforms such as AWS and GCP.

Experience with data visualization tools like Tableau and Power BI.

Strong understanding of data preprocessing, feature engineering, and model evaluation.

Excellent communication and collaboration skills to work with cross-functional teams.

Ability to work in an agile environment and adapt to changing priorities.

Strong problem-solving skills and attention to detail.

Experience with containerization using Docker and Kubernetes.

Familiarity with DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines.