Senior Data Scientist
Pune, Maharashtra, India
- Remote-first
- Website
- @weekdayworks 𝕏
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Weekday
At Weekday, we help companies hire engineers who are vouched by other software engineers. We are enabling engineers to earn passive income by leveraging & monetizing the unused information in their head about the best people they have worked...This role is for one of Weekday’s clients
Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA)
Min Experience: 5 years
Location: Pune, Bengaluru
JobType: full-time
Requirements
About the Role:
We are seeking a highly skilled and innovative Senior Data Scientist to join our advanced analytics team. In this role, you will leverage your expertise in Python, Natural Language Processing (NLP), and Large Language Models (LLMs) to build, deploy, and optimize AI-powered solutions that drive business insights and improve product functionality. You will work closely with cross-functional teams, including engineering, product, and domain experts, to translate complex business challenges into robust machine learning models.
This is a high-impact role for someone who thrives in a data-driven environment and is passionate about solving real-world problems through intelligent systems and cutting-edge data science techniques.
Key Responsibilities:
- Design, develop, and deploy scalable data science solutions, focusing on natural language processing (NLP) and large language models (LLMs).
- Apply machine learning and deep learning algorithms to extract insights from structured and unstructured datasets.
- Develop custom NLP pipelines for tasks such as sentiment analysis, topic modeling, named entity recognition, and text summarization.
- Fine-tune, evaluate, and deploy LLMs like GPT, BERT, or similar to solve domain-specific problems.
- Collaborate with data engineers to build and maintain robust data pipelines for training and production environments.
- Work with product and business teams to identify opportunities where data science can deliver business value.
- Communicate technical findings and insights to non-technical stakeholders in a clear and actionable manner.
- Stay up-to-date with the latest advancements in AI/ML, NLP, and LLM research and apply relevant techniques to ongoing projects.
- Lead and mentor junior data scientists in best practices for model development, validation, and deployment.
Required Skills & Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. PhD preferred.
- Minimum of 5 years of hands-on experience in data science or applied machine learning.
- Strong proficiency in Python and related libraries such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, and spaCy.
- Demonstrated experience in NLP techniques and language model fine-tuning, including experience with Hugging Face Transformers or OpenAI APIs.
- Solid understanding of machine learning theory, model evaluation, and feature engineering.
- Experience working with cloud platforms such as AWS, GCP, or Azure for scalable model deployment.
- Familiarity with version control (Git), collaborative workflows, and agile development.
- Excellent communication skills with the ability to present complex technical concepts to diverse audiences.
- Strong analytical mindset with a focus on delivering measurable business outcomes.
Nice to Have:
- Experience with vector databases (e.g., FAISS, Pinecone) and semantic search implementations.
- Familiarity with LLMOps, prompt engineering, and conversational AI systems.
- Experience in deploying and maintaining ML models in production environments.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs AWS Azure BERT Computer Science Conversational AI Data pipelines Deep Learning Engineering FAISS Feature engineering GCP Git GPT LLMOps LLMs Machine Learning Mathematics ML models Model deployment NLP NumPy OpenAI Pandas PhD Pinecone Pipelines Prompt engineering Python PyTorch Research Scikit-learn spaCy Statistics TensorFlow Topic modeling Transformers
Perks/benefits: Career development
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