Gen AI/ ML Data Scientist

KEY RESPONSIBILITIES: Data Science: Develop machine learning models to support recommendation systems and NLP projects Provide actionable insights for product and service optimization Data Engineering: Build and maintain scalable ETL pipelines Optimize data storage solutions (data lakes, columnar formats) and ensure data accuracy for analytics Data Analysis & Insight Generation: Analyze complex datasets to uncover trends and patterns Generate and present insights that drive strategic decisions and enhance client services Stakeholder Collaboration: Work with product and service teams to understand data needs and translate them into technical solutions Working Relationships: Reporting to: VP Business Growth External Stakeholders: Clients Skills/Competencies Required: Technical Skills: Proficiency with Python (Pandas, NumPy), SQL , and Java Experience with LLMs , Lang Chain , and Generative AI technologies Familiarity with ML frameworks (Tensor Flow, PyTorch) and data engineering tools (Spark, Kafka) Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders Proficient in key data engineering concepts , such as data lakes , columnar formats , ETL tools , and BI tools Knowledge in Machine Learning , NLP , Recommender systems , personalization , Segmentation , microservices architecture , and API development Ability to adapt to a fast-paced , dynamic work environment and quickly learn new technologies Soft Skills: Work well in a team or independently Excellent written & verbal communication skills Strong critical thinking and questioning skills High degree of flexibility willing to fill in the gaps rather than relying on others Strong communication skills, especially in presenting data insights Flexibility, problem-solving, and a proactive approach in a fast-paced environment Academic Qualifications & Experience Required: Required Educational Qualification & Relevant Experience: Bachelor's Degree in Computer Science , Data Analytics , Engineering , or a related field Minimum 3 to 5 years of experience in data science and data engineering Strong critical thinking abilities and capacity to work autonomously Proficient understanding of key data engineering concepts (data lakes, columnar formats, ETL tools, and BI tools) High motivation , good work ethic , maturity, and personal initiative Strong oral and written communication skills