Quadratyx is looking for a DevOps Engineer to support our rapidly-growing development organization and cloud infrastructure. As a company theory we're embracing the total-ownership model with engineers oncall for their own services in a supportive and collaborative environment. The DevOps team is a crucial partner in building a reliable and scalable product for our customers and a sustainable work environment for our product and engineering teamsJob / Role InformationDesignation
- Lead Data Scientist – PhD/Tier 1 | Corporate Experience
Experience
Function
- AI & Data Science Enterprise Delivery
Location
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.
Working Relationships
Reporting to
- Project Manager / Team Lead
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).
- 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
Academic Qualifications & Experience Required
Required Educational Qualification & Relevant Experience
- Bachelor’s 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.Interested candidate profiles should be emailed to jobs@quadratyx.com