Lead Data Scientist

EPAM Systems; México; Remote; MXN 900,000 - 1,500,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off and sick leave

Upskilling and certification courses

LinkedIn Learning access

Job summary

EPAM Systems in Mexico seeks an experienced Lead Data Scientist to drive data-driven initiatives across business and technology teams. You will design and implement analytical models and collaborate with stakeholders to deliver high-impact solutions.

You will mentor junior staff, stay current with AI methods, and contribute to strategic data projects. Fluency in English and strong Python/Java skills are essential for this role.

Qualifications

• Minimum 5 years of professional data science experience.
• Hands-on experience with AI concepts and tools.
• Strong mathematics, statistics, and computer science foundations.
• Proficient in Python; Java for data-related applications.

Responsibilities

• Design and implement analytical models for business goals.
• Collaborate with cross-functional teams to ensure timely delivery.
• Participate in strategic discussions guiding data initiatives.
• Evaluate colleagues' work and provide constructive feedback.
• Document methodologies and findings for long-term knowledge transfer.
• Stay updated with emerging data science trends.

Skills

5+ years experience

AI concepts

Analytical thinking

English communication

Mentoring juniors

Cross-functional collaboration

Tools

Python

Java

Data processing

Job description

We're seeking an experienced Lead Data Scientist to become part of our organization. In this position, you'll have the chance to engage in purposeful, data-centered initiatives inside a cooperative and innovative setting. As a team member, you'll join colleagues who prioritize analytical precision, ongoing education, and the hands-on use of current technology. For those enthusiastic about extracting insights from intricate data and helping build impactful solutions, this role provides a solid foundation for career development.ResponsibilitiesDesign and implement analytical models addressing business and technical goalsPartner with cross-functional teams to ensure deliverables are finished punctually and meet quality benchmarksParticipate in strategic conversations, providing input that helps guide data-focused initiativesEvaluate colleagues' work, offering constructive feedback to maintain sound analytical standardsExplore and address complex analytical issues that emerge during the project lifecycleHelp junior team members grow by sharing knowledge that builds their capabilitiesEngage in planning sessions, helping define scope and offering accurate time estimatesKeep up with emerging trends in the field and incorporate useful new methods into daily tasksKeep thorough documentation of essential methodologies and findings to enable long-term knowledge transferCollaborate closely with stakeholders to set clear goals and ensure finished work meets expectationsRequirementsAt least 5 years of relevant professional experienceHands-on familiarity with AI concepts and tools, used to improve analytical solutionsRobust background in Data Science, capable of deriving meaningful insights from complex datasetsSkilled in Python for creating and deploying data-driven models and solutionsBackground in Java for building and integrating data-related applicationsStrong grounding in Mathematics, Statistics, and Computer Science to underpin rigorous analytical workFluent English communication abilities at B2 level or aboveWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.