Machine Learning Engineer, Data Scientist, or Data Analyst

HCLTech is a global technology company, home to more than 226,500\+ people across 60 countries, delivering industry-leading capabilities centered around AI, digital, engineering, cloud and software, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, High Tech, Semiconductor, Telecom and Media, Retail and CPG, Mobility and Public Services.

HCLTech is seeking a skilled

Machine Learning Engineer, Data Scientist, or Data Analyst

to design, develop, and deploy machine learning models, conduct deep data analysis, and generate actionable insights.

Exp: 8- 12 years

Location: Bengaluru /Chennai /Hyderabad /Noida/Pune

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: Strong 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.
• SQL \& Databases: Proficiency in SQL for querying relational databases and working with NoSQL databases (e.g., MongoDB, BigQuery).
• Version Control: Experience using Git for version control.

Tools \& Technologies:

• Machine Learning: Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost.
• Data Analysis: Pandas, NumPy, Matplotlib, Seaborn, Plotly.
• Cloud Platforms: AWS, Google Cloud, Azure.
• Databases: MySQL, PostgreSQL, MongoDB, BigQuery, Snowflake.
• Data Visualization: Tableau, Power BI, Matplotlib, Seaborn, Plotly.
• Version Control: Git.

If above opportunity is in line with your profile and who can join us in shorter notice, please drop your updated resume to [email protected]/[email protected]