Data Scientist

Talent Corner Hr Services; Pune District; On-site; INR 800,000 - 1,200,000; Full time

Job summary

Talent Corner Hr Services is seeking an experienced Data Scientist for our Kandivali position. You will build and deploy ML models, perform data preprocessing, feature engineering, and model training while integrating solutions via Python APIs.

The role emphasizes production-grade AI, not just model prototyping. You should bring 3+ years of data science experience with strong Python skills, ML techniques, and experience deploying end-to-end pipelines.

Qualifications

• 3+ years of data science experience
• Strong Python programming and ML model development
• Experience with end-to-end ML pipelines and production deployment

Responsibilities

• Develop and deploy machine learning and deep learning models.
• Data preprocessing, feature engineering, and model training.
• Perform feature selection and hyperparameter tuning to optimize model performance.
• Build and optimize end-to-end ML pipelines.
• Integrate ML models into applications using Python APIs (FastAPI/Flask).
• Work with large datasets using SQL and Python.
• Evaluate models using appropriate metrics and improve their accuracy, scalability, and reliability.
• Monitor model performance in production, identify model drift, and implement retraining strategies.
• Collaborate with backend and product teams for AI integration.
• GenAI/LLM-based solutions work (optional but preferred).

Skills

Python programming

Machine Learning

Feature engineering

Hyperparameter tuning

End-to-end ML pipelines

SQL

Tools

Scikit-learn

Pandas

NumPy

TensorFlow

PyTorch

Job description

Data Scientist - Kandivali

Exp - 3+
Budget - 10

Location - Mumbai,Kandivali onsite

Pref - male candidates

"Job Overview
We are looking for an experienced Data Scientist (ML) to build and deploy intelligent systems using machine learning, deep learning, and GenAI techniques. The role focuses on production-grade AI solutions, not just model building.

• Responsibilities
  Develop and deploy machine learning and deep learning models.
  Work on data preprocessing, feature engineering, and model training.
  Perform feature selection and hyperparameter tuning to optimize model performance.
  Build and optimize end-to-end ML pipelines.
  Integrate ML models into applications using Python APIs (FastAPI/Flask).
  Work with large datasets using SQL and Python.
  Evaluate models using appropriate metrics and improve their accuracy, scalability, and reliability.
  Monitor model performance in production, identify model drift, and implement retraining strategies.
  Collaborate with backend and product teams for AI integration.
  Work on GenAI / LLM-based solutions (optional but preferred).
  
• Required Skills
  Strong in Python programming.
  Machine Learning: Regression, Classification, Clustering, Ensemble Learning (Random Forest, XGBoost, LightGBM).
  Strong understanding of feature engineering, feature selection, and hyperparameter tuning.
  Proficiency in model evaluation techniques including Accuracy, Precision, Recall, F1-Score, ROC-AUC, and Cross Validation.
  Libraries: Scikit-learn, Pandas, NumPy.
  Basic Deep Learning: TensorFlow or PyTorch (good to have).
  Strong SQL and data handling skills.
  Understanding of model deployment and production monitoring.
  Experience building end-to-end ML pipelines from data preprocessing to deployment.
  
• Good to Have
  Experience with LLMs / GenAI (OpenAI, LangChain, Hugging Face).
  Knowledge of MLOps (Docker, Kubernetes, MLflow).
  Cloud platforms (AWS / Azure / GCP).
  Experience in API development (FastAPI / Flask).
  Must Have Mindset
  Strong problem-solving and analytical thinking.
  Production-focused (not only research work).
  Ability to handle real-world messy data.
  Ownership of end-to-end AI solutions.