About the Role :

We are looking for a Senior Data Scientist to lead the design and development of intelligent, data-driven systems that power talent discovery, candidate-job matching, and workforce insights. In this role, you'll build and deploy models that process unstructured data at scale, extract actionable insights, and deliver real-time recommendations to enhance decision-making across the talent lifecycle.

If you're passionate about building smart systems that solve real-world problems in the intersection of data, people, and technology this is your calling.

Key Responsibilities :

- Build and optimize machine learning models for use cases like candidate-job matching, resume parsing, talent ranking, recommendation systems, and profile enrichment.

- Apply NLP techniques to extract and analyze insights from large volumes of unstructured data (resumes, job descriptions, interviews, etc.).

- Lead experimentation efforts including A/B testing, model comparisons, and business metric evaluation.

- Collaborate with product, engineering, and data teams to productionize ML pipelines and ensure model reliability at scale.

- Develop interpretable models and frameworks that deliver explainable AI (XAI) capabilities.

- Identify and evaluate data sources (internal & external) for enhancing model performance and domain coverage.

- Design and maintain systems to monitor model drift, retraining workflows, and feature performance in production.

Must-Have Skills :

- 5+ years of hands-on experience in data science or machine learning roles, ideally in search, recommendation, or NLP-focused systems.

- Strong proficiency in Python, including packages like scikit-learn, spaCy, transformers, pandas, NumPy, TensorFlow, or PyTorch.

- Experience with natural language processing (NLP), including named entity recognition, embeddings, text classification, and semantic search.

- Solid experience working with structured and unstructured data, and building scalable data pipelines.

- Strong command over SQL and experience with distributed data systems (e.g., Snowflake, BigQuery).

- Demonstrated experience taking models from experimentation to production, with clear metrics and monitoring in place.

- Excellent problem-solving and communication skills with the ability to work cross-functionally.

Nice-to-Have Skills :

- Knowledge of recommendation engines, graph-based models, or search ranking algorithms.

- Exposure to cloud platforms like AWS, Azure, or GCP, and MLOps workflows (CI/CD for models).

- Experience in talent tech, HR tech, or recruitment intelligence platforms is a strong plus.

- Familiarity with vector databases, embeddings, and semantic similarity search.