Data Scientist - Machine Learning/Artificial Intelligence (2-4 yrs)

Company Profile :

Our Client is a premier software services company specializing in digital transformation and enterprise reinvention, delivering end-to-end results to clients across diverse sectors. They have dynamic suite of advanced solutions built on Generative AI, Machine Learning, Data Science, Industry Data Models, Infrastructure & Database Migration, SAP Extend & Innovate, App Modernization, and Enterprise Cloud Integration, positions us at the nexus of traditional enterprise systems and modern cloud innovation. With a global presence spanning the USA, India, APAC, UAE, Europe, and Canada. It has boasts a dedicated workforce of over 2000+ professionals that serve up an impressive client base, including 90% of Fortune 500 companies, guiding them through their transformative digital journeys.

Position Title : Data Scientist

Qualifications : Bachelor's/Master's degree in Computer Science, Data Science, or related field.

Experience : 2-4 Years

Job Location : Pune

Job Summary :

Our client are seeking an innovative and highly skilled Data Scientist with 2-4 years of experience in cutting-edge machine learning and AI solutions. The ideal candidate will demonstrate a strong foundation in classical machine learning, advanced time series analytics, and proficiency in implementing state-of-the-art Generative AI and multimodal models. Expertise in migrating ML workflows (e.g., SageMaker to Databricks), leveraging the Databricks Lakehouse Platform, and deploying solutions on Azure ML is essential.

Job Description :

- Build, train, and fine-tune machine learning models, including classical ML, deep learning, and advanced time series models.

- Collaborate with cross-functional teams to collect, preprocess, and manage structured and unstructured data.

- Design and deploy scalable and efficient data science pipelines for production environments.

- Build and optimize scalable ML pipelines for production use.

- Lead or support migration of ML models and workflows across cloud platforms, ensuring alignment with organizational goals.

- Maintain a strong focus on innovation, leveraging the latest advancements in AI and ML to address business challenges.

- Present insights and recommendations to technical and non-technical stakeholders to drive decision-making.

- Leverage Databricks Lakehouse capabilities for feature engineering and model deployment.

- Lead the migration of ML models from platforms like AWS SageMaker to Databricks, optimizing for performance, scalability and cost optimization.

- Experiment and build generative AI applications and multimodal models to address real-world problems.

- Develop creative AI-powered solutions integrating text, image, and numerical data sources.

- Partner with data engineers, architects, and product managers to ensure model compatibility with the architecture.

- Communicate data-driven insights and actionable solutions effectively to technical and non-technical teams.

- Optimize model performance and ensure seamless integration with existing systems and platforms.

- Stay updated with industry trends and contribute to the continuous improvement of data science practices.

Required Skills Set :

- Proficiency in classical machine learning and time series forecasting.

- Good understanding and hands-on of deep learning.

- Hands-on experience with model migrations.

- Expertise with Databricks Lakehouse platform.

- Strong skills in Generative AI (e.g., OpenAI, LLAMA) and multimodal models.

- Experience with Azure AI and ML services.

- Proficiency in Python (libraries like pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).

- Excellent problem-solving and debugging abilities.

- Understanding of explainable AI (XAI) concepts and best practices for AI governance.

- Good understanding and hands-on with MLops.

Preferred Skills Set :

- Certifications in Databricks or Azure.

- Familiarity with cloud cost optimization and resource management.

- Excellent communication and documentation skills for client-facing engagements.

- Experience with AWS and GCP.