Designation : Data Science Engineer

Location : Bengaluru

Experience : 0 - 1 years

Function : AI & Data Science

Role Description :

We are looking for a Data Science Engineer to join our small, high-ownership AI & Data Science team. You will help build and ship the ML models and AI features that power our CDP platform, from customer segmentation and entity resolution to predictive analytics and LLM-powered automation. This is a hands-on engineering role : your work goes to production, not into notebooks that stay in research. You will learn by shipping, with mentorship from senior team members.

Key Responsibilities :

- Build and evaluate customer segmentation and clustering models (K-Means, DBSCAN, hierarchical) under guidance from senior team members

- Support the development of entity resolution pipelines, using fuzzy matching, blocking and scoring to unify customer profiles across data sources

- Train and evaluate predictive models for churn, conversion propensity and recommendations (logistic regression, Random Forest, XGBoost)

- Help build LLM-powered features such as schema mapping, natural language querying and insight generation, using prompt engineering, embeddings and RAG pipelines through LLM APIs

- Write SQL for feature engineering on analytical databases such as Snowflake or BigQuery

- Wrap models in APIs (FastAPI) and help containerize and deploy them for batch and real-time inference

- Contribute to monitoring, retraining and versioning of models in production

- Work with data engineers to keep training data and feature pipelines clean and reliable

- Document your experiments, assumptions and results clearly

Experience and Skills :

- Solid Python fundamentals, with working knowledge of Pandas, NumPy and scikit-learn

- Good understanding of core ML concepts : supervised vs. unsupervised learning, overfitting, cross-validation, and precision/recall trade-offs

- Comfortable with SQL beyond basic SELECT : joins, aggregations and an introduction to window functions

- Basic understanding of text embeddings and semantic similarity

- Familiarity with calling LLM APIs (Claude, OpenAI or similar) and writing effective prompts

- Basic exposure to REST APIs (FastAPI or Flask) and Git

- Strong problem-solving ability and a willingness to learn quickly

Good to Have :

- Hands-on exposure to XGBoost, or to Hugging Face transformers or sentence-transformers

- Basic familiarity with Docker

- Exposure to vector search (FAISS, Pinecone) or frameworks like LangChain

- Familiarity with MLflow or other experiment tracking tools

- Knowledge of fuzzy matching (Levenshtein, Jaro-Winkler) or record linkage

- Academic projects, internships, Kaggle entries or GitHub work that show applied ML skills

- Interest in customer analytics or MarTech

Qualifications :

- B.E./B.Tech/M.Tech/M.Sc. in Computer Science, Data Science, Statistics, Mathematics or a related field

- 0 - 1 year of relevant experience, including internships and substantial personal or academic projects