Senior Data Scientist

Purpose of the Job/ Role :

KEY RESPONSIBILITIES

Delivery & Project Leadership:

• Translate business goals into sprint-level roadmaps,
• Lead design/code reviews; enforce git-flow, CI/CD and documentation standards.
• Chair weekly steering meetings; secure production acceptance and SLA sign-off.

Data Science & Engineering:

• Build ML, NLP and recommender models; oversee feature pipelines and data-quality gates.
• Implement full MLOps lifecycle (Docker, Kubernetes, MLflow/Kubeflow); set up drift & latency monitoring.
• Design scalable ETL on AWS / Azure / GCP.

Team Leadership & Mentoring:

• Coach and grow a 4-8-member DS/DE squad via code reviews, pair programming and brown-bag sessions.
• Drive hiring, onboarding and performance reviews; foster a culture of experimentation + production discipline.

Stakeholder & Client Engagement:

• Act as primary contact for client data-science initiatives, present insights to exec & non-tech audiences.
• Support pre-sales with PoCs, effort estimates and Statements of Work.

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).
• 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 &

• Bachelors Degree in Computer Science, Data Analytics, Engineering, or a related field from a Tier 1 institute or a Ph.D. in a relevant discipline.
• Corporate experience is mandatory.
• Minimum of 8 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.