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EPAM Systems

Data Science Consultant

mexico / Posted
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EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

 

 

We are on the lookout for a Data Science Consultant to grow our remote team. This role suits individuals dedicated to leveraging data to solve business challenges and skilled at managing projects from initiation to completion. As a Data Science Consultant, you will play a central role in turning data into impactful insights that guide strategic decisions.

 

Responsibilities

  • Lead the development and implementation of ML/AI solutions, offering both technical leadership and strategic guidance
  • Design responsible AI systems, tailoring solutions to client requirements through detailed planning and precise evaluation approaches
  • Promote AI adoption across organizational divisions by introducing new products and solutions
  • Illustrate how ML/AI solutions effectively address client business challenges
  • Collaborate with data scientists and engineers while offering leadership and mentorship to strengthen team expertise
  • Stay informed about emerging ML/AI technologies and advocate for innovative practices aligned with regulatory standards
  • Align business, legal, and technical stakeholders to streamline project progress and ensure seamless communication
  • Develop ML solutions, define project scopes, and manage teams throughout the sales-to-delivery timeline
  • Strengthen client relationships by maintaining effective communication and ensuring client satisfaction
  • Engage senior-level client stakeholders to foster AI integration across their organizations
  • Assist sales and pre-sales activities by assessing data opportunities, responding to RFPs, and creating proposal presentations

Requirements

  • 8+ years of experience in IT with a strong background in Data Science
  • 3+ years in leadership roles such as Lead, Manager, or Architect within Agile or hybrid environments
  • Experience managing teams of 20 or more members
  • Completion of at least 5 full project cycles or major product launches
  • Extensive leadership expertise in Data Analytics, Machine Learning, and AI
  • Track record of designing and deploying ML/AI solutions
  • Knowledge of Machine Learning, including deep learning, statistical approaches, and various ML models
  • Capability to engage senior stakeholders and secure project support or funding
  • Strong communication skills for explaining complex technical topics to varied audiences
  • Proficiency in Python and ML frameworks like PyTorch or TensorFlow
  • Flexibility to translate intricate business needs into actionable ML/AI solutions
  • Understanding of regulatory processes from experiences in heavily regulated industries or technology roles
  • Familiarity with cloud platforms such as AWS, Azure, or GCP
  • Advanced proficiency in English for effective communication and client engagement

Nice to have

  • Showcase of certifications in Data Science or Machine Learning
  • Background in public speaking or delivering workshops focused on AI-related subjects

 

We offer

  • International projects with top brands
  • Work with global teams of highly skilled, diverse peers
  • Healthcare benefits
  • Employee financial programs
  • Paid time off and sick leave
  • Upskilling, reskilling and certification courses
  • Unlimited access to the LinkedIn Learning library and 22,000+ courses
  • Global career opportunities
  • Volunteer and community involvement opportunities
  • EPAM Employee Groups
  • Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn