Gen AI | ML- Data Scientist- ( Lead)

This role is responsible for managing the client expectations. Strategize with various stakeholders to meet customer requirements.

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 and Insight Generation:

  Skilled in analyzing complex datasets to uncover trends and patterns; generate and present insights that drive strategic decisions and enhance client services.

Stakeholder Collaboration:

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 (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka).
• Microservices, CI CD, ML
• Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders.
• Proficient understanding of 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 learn new technologies quickly.

Soft Skills

• Work in a team/ Independently.
• Excellent Written & Verbal Communication Skills
• Solid 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

Required Educational Qualification & Relevant

Experience

• Bachelors Degree in Computer Science, Data Analytics, Engineering, or a related field.
• Minimum of 5 to 10 years of experience in data science and data engineering.
• Strong critical thinking abilities and the capacity to work autonomously.
• Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools High motivation, good work ethic, maturity and personal initiative.
• Strong oral and written communication skills.

Quadratyx is an equal opportunity employer - we will never differentiate candidates on the basis of religion, caste, gender, language, disabilities or ethnic group. Quadratyx reserves the right to place/move any candidate to any company location, partner location or customer location globally, in the best interest of Quadratyx business.