We are looking for experienced Data Scientists and Lead Data Scientists with a strong background in FinTech, Banking, and Financial Services. The ideal candidate will have proven expertise in machine learning, NLP, and deep learning, along with hands-on experience applying these techniques to real-world financial datasets and business problems.

Location : Gurgaon

Education : Any Engineering Graduation or Master's from premium institute

Key Responsibilities :

- Design, develop, and deploy machine learning and deep learning models for real-world applications.

- Perform data wrangling, including cleaning, transformation, and feature engineering from diverse sources.

- Conduct exploratory data analysis and create insightful visualizations to communicate findings.

- Fine-tune and optimize models, including adaptation of pre-trained architectures.

- Collaborate with cross-functional teams to understand project requirements and deliver scalable solutions.

- Maintain version control using Git and interact with databases for data retrieval and storage.

- Stay current with advancements in AI, particularly in NLP and large language models.

Must-Have Skills :

- Proficiency in Python programming for data science tasks.

- Hands-on experience with Machine Learning & Deep Learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

- Strong background in Natural Language Processing (NLP), including text preprocessing and model implementation.

- Experience in model training and fine-tuning, including hyperparameter optimization.

- Expertise in data wrangling - cleaning, transforming, and preparing complex datasets.

- Skill in data visualization using libraries such as Matplotlib, Seaborn, or Plotly.

- Working knowledge of Git for version control and database management (SQL or NoSQL).

- Ability to quickly grasp project requirements and adapt to evolving technical and business needs.

Good-to-Have Skills :

- Experience in prompt engineering and integrating LLMs (e.g., GPT, Llama) into applications.

- Strong foundation in statistics and mathematics relevant to machine learning.

- Exposure to cloud platforms such as AWS, GCP, or Azure (e.g., for model deployment or data processing).

- Prior experience mentoring junior team members (especially for Lead role).