Job Title: Data Scientist ML Engineering

Experience - 3 - 8 Years

Immediate Joiners Preferred.

Location: Bengaluru

We are looking for a Data Scientist with 3 - 8 years of experience in Machine Learning Engineering and Time Series Forecasting. The ideal candidate should have hands-on experience in developing, deploying, and monitoring machine learning models in production environments, with a strong foundation in statistics, data science, and software engineering.

Key Responsibilities

- Design, develop, and deploy scalable machine learning models for business use cases.
- Build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
- Develop and optimize time series forecasting models for demand forecasting, anomaly detection, or predictive analytics.
- Work with structured and unstructured datasets to extract actionable insights.
- Collaborate with cross-functional teams including Product, Engineering, and Business stakeholders.
- Implement model monitoring, retraining strategies, and performance optimization.
- Ensure code quality, reproducibility, and best practices using version control and CI/CD pipelines.

Required Skills

- 3 - 8 years of experience in Data Science and Machine Learning.




- Strong proficiency in Python and ML libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
- Hands-on experience with Time Series Forecasting techniques (ARIMA, SARIMA, Prophet, LSTM, Transformer-based models, etc.).
- Experience with ML Engineering concepts including model deployment, MLOps, Docker, Kubernetes, MLflow, or similar tools.
- Strong understanding of statistics, probability, and machine learning algorithms.
- Experience with SQL and data manipulation using Pandas, NumPy.
- Familiarity with cloud platforms (AWS, Azure, or GCP) is preferred.
- Knowledge of Spark/PySpark is an added advantage.

Preferred Qualifications

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
- Experience in production-grade ML systems and scalable data pipelines.
- Solid problem-solving and communication skills.

Nice to Have

- Experience with GenAI/LLMs and Retrieval-Augmented Generation (RAG).
- Exposure to MLOps frameworks and workflow orchestration tools such as Airflow or Kubeflow.
- Experience with experimentation, A/B testing, and model explainability.

📌 Data Scientist (Bengaluru)
🏢 Bct Consulting
📍 Bengaluru