Data Scientist - Contract

About Prismforce

Prismforce is a Vertical SaaS company revolutionizing the Talent Supply Chain for global Technology, R&D/Engineering, and IT Services companies. Our AI-powered product suite enhances business performance by enabling operational flexibility, accelerating decision-making, and boosting profitability. Our mission is to become the leading industry cloud/SaaS platform for tech services and talent organizations worldwide.

Job Description

**Job Title**: Data Scientist

• Experience**: 1–3 years
• Location**: Bangalore
• Team**: AI & ML
  
  

### 🔍 About the Role

We are looking for a Data Scientist with strong fundamentals in **NLP** and **machine learning** to help build custom AI solutions for real-world talent intelligence problems. You will work across the stack — from data exploration and model development to evaluation and deployment — with a focus on building robust, scalable systems using state-of-the-art techniques.

### 🔧 Responsibilities

• Develop and fine-tune models for **NER**, **text classification**, **semantic similarity**, and **clustering**
• Work with **pretrained embeddings**, **transformers**, and **LLMs** to extract and normalize structured data from messy text
• Design and run experiments to evaluate model performance and guide improvements
• Collaborate with product and engineering to turn models into robust, production-ready solutions
• Continuously explore research and open-source tools to improve performance and scalability
  
  

### ✅ Requirements

• 1–3 years of hands-on experience in **applied NLP and ML**
• Strong coding skills in **Python**, and experience with **Pandas**, **Scikit-learn**, **PyTorch** or **TensorFlow**
• Familiarity with modern NLP toolkits: **Spacy**, **HuggingFace Transformers**, **SBERT**, etc.
• Solid understanding of **embedding models**, **attention mechanisms**, and **evaluation metrics**
• Ability to break down abstract problems and build custom, data-driven solutions
  
  

### ⭐ Nice to Have

• Experience with **LLM APIs**, **prompt engineering**, or **metadata generation using LLMs**
• Exposure to **knowledge graphs**, **taxonomy design**, or **vector databases**
• Contributions to open-source NLP tools or research projects