Experince-7 Yrs

Job Location- Hyderabad/ Bangalore

Key Responsibilities:

- Data Preparation & Analysis:
- Gather, clean, and preprocess structured, semi-structured, and unstructured data from various sources.
- Conduct exploratory data analysis (EDA) to identify trends, patterns, and outliers.
- Apply data wrangling techniques using Pandas, NumPy, and SQL to transform raw data into usable formats.
- Use statistical analysis to drive data-driven decision-making.

- Machine Learning Model Development
- Build, train, and fine-tune machine learning models using Scikit-learn, TensorFlow, Keras, or PyTorch.
- Develop predictive models, classification algorithms, clustering models, and recommendation systems.
- Conduct hyperparameter optimization using techniques like grid search or random search.
- Model Evaluation & Optimization:
- Evaluate model performance using metrics such as Accuracy, Precision, Recall, F1-Score, AUC-ROC, Confusion Matrix, and Cross-validation.
- Improve model performance through techniques such as feature engineering, data augmentation, and regularization.
- Deploy models into production environments, and monitor performance for continual improvement.
- Data Visualization & Reporting:
- Develop dashboards and reports using Tableau, Power BI, Matplotlib, Seaborn, or Plotly.
- Present findings through clear visualizations and actionable insights to non-technical stakeholders.
- Write detailed reports on data analysis and machine learning results, ensuring transparency and reproducibility.




- Collaboration & Stakeholder Communication:
- Work closely with cross-functional teams (e.g., engineering, product, business) to define data-driven solutions.
- Communicate technical concepts clearly to non-technical stakeholders and provide insights that influence product and business strategy.
- Data Pipeline & Automation:
- Design and implement scalable data pipelines for model training and deployment using Airflow, Apache Kafka, or Celery.
- Automate data collection, preprocessing, and feature extraction tasks.
- Research & Continuous Learning:
- Stay up-to-date with the latest trends in machine learning, deep learning, and data science methodologies.
- Explore new tools, techniques, and frameworks to improve model accuracy and efficiency.

Required Skills:

- Programming Languages: Robust proficiency in Python, with experience in SQL.
- Machine Learning: Hands-on experience with Scikit-learn, TensorFlow, Keras, PyTorch, or similar ML libraries.
- Data Analysis: Strong skills in Pandas, NumPy, and Matplotlib for data manipulation and analysis.
- Statistical Analysis: Experience applying statistical methods to data, including hypothesis testing and regression analysis.
- Cloud Platforms: Familiarity with AWS, Azure, or Google Cloud for deploying models and using cloud-native data services (e.g., AWS Sagemaker, Azure ML).
- Data Visualization: Experience using Tableau, Power BI, Matplotlib, Seaborn, or Plotly for creating visualizations.

📌 Machine Learning Engineer & Data Scientist (Bengaluru)
🏢 HCLTech
📍 Bengaluru