Sr. Data Scientist

at  Grid Dynamics

We are seeking a Senior Data Scientist with proven expertise in developing Machine Learning models, including tabular data and NLP models. The ideal candidate will have experience with product recommendation systems and the ability to innovate beyond traditional approaches. This role requires strong programming skills in Python, extensive experience with AWS cloud services (particularly SageMaker, EC2, S3, and Redshift), and a solid understanding of the full ML lifecycle and MLOps principles.

Essential functions

• Collaborate closely with the engineering and product team to design and implement Machine Learning models that support product recommendations and other business needs
• Develop and manage the Machine Learning lifecycle, from initial prototyping to full-scale production deployment
• Interpret and integrate complex data sets from various sources, including structured and unstructured data
• Apply expert knowledge in Machine Learning and Artificial Intelligence to diverse datasets and use cases, ensuring scalability and adaptability of solutions based on volume and requirements
• Build and maintain a robust MLOps workflow, including model prototyping, deployment, and monitoring.

Qualifications

• Proven expertise in developing Machine Learning models, including tabular data and NLP models
• Experience with product recommendation systems and the ability to innovate beyond traditional approaches.
• Experience with AWS cloud services, particularly SageMaker, EC2, S3, and Redshift.
• Strong programming skills in Python
• Experience in deploying Machine Learning models into production environments, particularly using CI/CD frameworks
• Solid understanding of the full ML lifecycle and MLOps principles
• Demonstrated ability to work collaboratively in cross-functional teams and communicate complex technical information to non-expert stakeholders.

We offer

• 100% payroll scheme, benefits by law (IMSS, INFONAVIT, 12+ vacation days)
• Benefits above the law: Vacation premium 50%, 5 PTOs, 3 sick days, 10 guaranteed public holidays per year
• Major medical insurance, Dental and Vision plan for an employee and direct family members
• Minor Medical Insurance (Multiservicios Médicos Santander) for an employee and direct family members
• Life Insurance and funeral expenses
• 5% savings fund, uncapped (matched by the company in the end of the year)
• Grocery cards/vouchers (Vales de Despensa)
• 30 days End of the Year Bonus (Aguinaldo)
• Opportunity to work on bleeding-edge projects with a highly motivated and dedicated team all over the world
• Individual career development plan and support from the best experts
• Professional development opportunities (Linkedin Learning, Cloud certification programs, access to corporate LMS integrated with other learning platforms)
• Well-equipped office in a business area of Guadalajara (quiet room, games room, air hockey, PS5, Nintendo Switch and Xbox Series X, pool table, ping pong, snacks, smoothies, and much more)
• Corporate social events (yoga, massages, sport tournaments, discussion panels, technical talks, lunch & learns)
• Flexible working hours
• Opportunity to relocate to another country where the company’s offices are present.

About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization, and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India

• Collaborate closely with the engineering and product team to design and implement Machine Learning models that support product recommendations and other business needs
• Develop and manage the Machine Learning lifecycle, from initial prototyping to full-scale production deployment
• Interpret and integrate complex data sets from various sources, including structured and unstructured data
• Apply expert knowledge in Machine Learning and Artificial Intelligence to diverse datasets and use cases, ensuring scalability and adaptability of solutions based on volume and requirements
• Build and maintain a robust MLOps workflow, including model prototyping, deployment, and monitoring