Experience: 3 – 7 Years
Location: Chennai
Job Description:
- Statistical Modeling: Develop and implement core statistical models, including linear and logistic regression, decision trees, and various classification algorithms. Analyze and interpret model outputs to inform business decisions.
- Advanced NLP: Work on complex NLP tasks, including data cleansing, text preprocessing, and feature engineering. Develop models for text classification, sentiment analysis, and entity recognition.
- LLM Integration: Design and optimize pipelines for integrating Large Language Models (LLMs) into applications, with a focus on Retrieval-Augmented Generation (RAG) systems. Work on fine-tuning LLMs to enhance their performance on domain-specific tasks.
- ETL Processes: Design ETL (Extract, Transform, Load) processes to ensure that data is accurately extracted from various sources, transformed into usable formats, and loaded into data warehouses or databases for analysis.
- BI Reporting and SQL: Collaborate with BI teams to ensure that data pipelines support efficient reporting. Write complex SQL queries to extract, analyze, and visualize data for business intelligence reports. Ensure that data models are optimized for reporting and analytics.
- Data Storage and Management: Collaborate with data engineers to design and implement efficient storage solutions for structured datasets and semi-structured text datasets. Ensure that data is accessible, well-organized, and optimized for retrieval.
- Model Evaluation and Optimization: Regularly evaluate models using appropriate metrics and improve them through hyperparameter tuning, feature selection, and other optimization techniques. Deploy models in production environments and monitor their performance.
- Collaboration: Work closely with cross-functional teams, including software engineers, data engineers, and product managers, to integrate models into applications and ensure they meet business requirements.
- Innovation: Stay updated with the latest advancements in machine learning, NLP, and data engineering. Experiment with new algorithms, tools, and frameworks to continuously enhance the capabilities of our models and data processes.
Overall Experience: 5+ years of overall experience working in a modern software engineering environment with exposure to best practices in code management, devops and cloud data/ML engineering. Proven track record of developing and deploying machine learning models in production.
ML Experience: 3+ years of experience in machine learning engineering, data science with a focus on fundamental statistical modeling. Experience in feature engineering, basic model tuning and understanding model drift over time. Strong foundations in statistics for applied ML.
Data Experience: 1+ year(s) in building data engineering ETL processes, and BI reporting.
NLP Experience: 1+ year(s) of experience working on NLP use cases, including large scale text data processing, storage and fundamental NLP models for text classification, topic modeling and/or more recently, LLM models and their applications.
Core Technical Skills: Proficiency in Python and relevant ML and/or NLP specific libraries. Strong SQL skills for data querying, analysis, and BI reporting. Experience with ETL tools and data pipeline management.
BI Reporting: Experience in designing and optimizing data models for BI reporting, using tools like Tableau, Power BI, or similar.
Education: Bachelor’s or Master’s degree in Computer Science / Data Science, or a related field.
Send your resumes to: career@ceiyone.com; saranya.ravikumar@ceiyone.com
Note: Please include the role in the subject line of the email.
