We are looking for a motivated Data Scientist to join our dynamic AI team in Pune.
Build PoCs and MVPs for ML and GenAI projects
Build and deploy LLM, RAG and chatbot solutions
Collect, clean and preprocess data for model training
Evaluate and fine-tune models; monitor GenAI outputs for bias and hallucinations
Document model development processes, code and findings
From the employer’s posting
We are looking for a motivated Data Scientist to join our dynamic AI team in Pune. This role will focus on proving concepts through rapid prototypes and building Minimum Viable Products (MVPs) in context of machine learning (ML) and Generative AI (GenAI) solutions, including GenAI-based chatbots. The ideal candidate will have a strong foundation in data science, with hands-on experience in ML models, familiarity with GenAI based solutions, and a keen interest in emerging AI technologies.
Execute PoCs and MVPs for AI and ML projects, focusing on practical implementation.
Build and deploy GenAI solutions, such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and chatbots.
Collect, clean, and preprocess data to ensure quality inputs for model training.
Monitor GenAI outputs for issues such as bias, hallucinations, and accuracy.
Document model development processes, code, and findings for transparency and reproducibility.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
SQL
AWS
Azure
GCP
MLflow
Airflow
Matplotlib
PyTorch
scikit-learn
TensorFlow
Where the posting names them
Technical Skills:
- Proficient in Python and SQL for data manipulation and model development.
- Familiarity with ML frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch.
- Basic understanding of MLOps tools like MLflow, Airflow, or similar is an advantage.
- Exposure to cloud platforms (Azure, AWS, GCP) for AI/ML model deployment is a plus.
Soft Skills:
- Experience with data visualization tools (e.g., Matplotlib, Seaborn) and EDA techniques.
- Basic understanding of MLOps tools like MLflow, Airflow, or similar is an advantage.
- Exposure to cloud platforms (Azure, AWS, GCP) for AI/ML model deployment is a plus.
- Familiarity with ML frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch.
- Experience with data visualization tools (e.g., Matplotlib, Seaborn) and EDA techniques.
- Basic understanding of MLOps tools like MLflow, Airflow, or similar is an advantage.
- Proficient in Python and SQL for data manipulation and model development.
- Familiarity with ML frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch.
- Experience with data visualization tools (e.g., Matplotlib, Seaborn) and EDA techniques.
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Company
Listed as MDLN.
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
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About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
We are looking for a motivated Data Scientist to join our dynamic AI team in Pune. This role will focus on proving concepts through rapid prototypes and building Minimum Viable Products (MVPs) in context of machine learning (ML) and Generative AI (GenAI) solutions, including GenAI-based chatbots. The ideal candidate will have a strong foundation in data science, with hands-on experience in ML models, familiarity with GenAI based solutions, and a keen interest in emerging AI technologies.
Key Responsibilities:
AI & ML Model Development:
Execute PoCs and MVPs for AI and ML projects, focusing on practical implementation.
Develop and refine ML models, including supervised and unsupervised learning algorithms.
Build and deploy GenAI solutions, such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and chatbots.
Collaborate with AI Engineers to integrate models into enterprise applications.
Data Handling & Preprocessing:
Collect, clean, and preprocess data to ensure quality inputs for model training.
Conduct exploratory data analysis (EDA) to uncover insights and inform model development.
Work with Data Engineers to ensure smooth data pipelines and infrastructure.
Model Evaluation & Optimization:
Evaluate model performance using appropriate metrics and fine-tune algorithms for optimal results.
Monitor GenAI outputs for issues such as bias, hallucinations, and accuracy.
Implement feedback loops for continuous model improvement.
Collaboration & Documentation:
Work closely with the AI Lead and cross-functional teams to align projects with business objectives.
Document model development processes, code, and findings for transparency and reproducibility.
Contribute to the development of best practices and playbooks for AI and ML solutions.
Continuous Learning & Development:
Stay updated with the latest trends and advancements in AI, ML, and GenAI technologies.
Participate in team knowledge-sharing sessions and training opportunities.
Qualifications & Skills:
Education:
Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
Experience:
1-3 years of experience in data science, machine learning, or AI-related roles.
Hands-on experience with ML model development and deployment.
Exposure to GenAI technologies, including LLMs and chatbot development, is a plus.
Technical Skills:
Proficient in Python and SQL for data manipulation and model development.
Familiarity with ML frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch.
Experience with data visualization tools (e.g., Matplotlib, Seaborn) and EDA techniques.
Basic understanding of MLOps tools like MLflow, Airflow, or similar is an advantage.
Exposure to cloud platforms (Azure, AWS, GCP) for AI/ML model deployment is a plus.
Soft Skills:
Strong analytical and problem-solving skills.
Eagerness to learn and adapt in a fast-paced, evolving environment.
Detail-oriented with a focus on delivering high-quality work.
Click here to learn more about a career in IT at Medline!
Our benefit package includes health insurance, life and disability, 401(k) contributions, paid time off, etc., for employees working 30 or more hours per week on average. For a more comprehensive list of our benefits please click here. For roles where employees work less than 30 hours per week, benefits include 401(k) contributions as well as access to the Employee Assistance Program, Employee Resource Groups and the Employee Service Corp.
We’re dedicated to creating a Medline where everyone feels they belong and can grow their career. We strive to do this by seeking diversity in all forms, acting inclusively, and ensuring that people have tools and resources to perform at their best. Explore our Belonging pagehere.
Medline Industries, LP is an equal opportunity employer. Medline evaluates qualified individuals without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, age, disability, neurodivergence, protected veteran status, marital or family status, caregiver responsibilities, genetic information, or any other characteristic protected by applicable federal, state, or local laws.