Data Scientist

Roles and Responsibilities

• Lead end-to-end data science and machine learning projects including model development, optimization, and evaluation
• Perform data cleaning, feature engineering, and exploratory data analysis to derive actionable insights
• Translate business requirements into well-defined technical solutions and measurable deliverables
• Communicate project progress, results, and insights effectively to non-technical stakeholders
• Collaborate with data scientists, ML engineers, and software engineers to deliver high-quality solutions
• Design and implement scalable ML workflows and pipelines using MLOps best practices
• Develop and evaluate NLP and LLM-based solutions aligned with business use cases
• Monitor model performance using appropriate evaluation and monitoring metrics
• Ensure models and solutions are robust, reliable, and maintainable
• Stay current with emerging tools, algorithms, and techniques in machine learning and apply them within the organization

Job Requirements

• Strong experience and understanding of NLP and the Large Language Model ecosystem
• Proficiency in Python for data analysis and supervised and unsupervised machine learning tasks
• Ability to convert complex machine learning problem statements into structured requirements and deliverables
• Experience working with at least one major cloud platform such as AWS, Azure, or GCP
• Working knowledge of SQL and NoSQL databases
• Experience creating reusable and efficient data and ML pipelines using MLOps principles
• Strong understanding of model evaluation, validation, and monitoring techniques
• Ability to work independently while effectively collaborating with cross-functional and global teams
• Excellent analytical, problem-solving, and communication skills

Good to Have

• Proven experience deploying machine learning models into production environments
• Experience building conversational AI solutions or chatbots
• Hands-on experience with open-source and closed-source LLMs
• Familiarity with frameworks and tools such as scikit-learn, BERT, LangChain, and Autogen
• Relevant certifications or formal training in data science or machine learning

Education

• Bachelor's, Master's, or PhD degree in Computer Science, Engineering, Data Science, or a related field