обновлено 4 дня назад
Lead Data Scientist (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead Data Scientist (AI): Leading a small ML squad embedded in client product teams to turn business problems into shippable models with an accent on demand forecasting, image insight extraction, and large-scale document processing. Focus on growing the team, translating customer needs into technical solutions, shaping project proposals, and contributing hands-on across generative AI, NLP, computer vision, and time series forecasting.
Location: Uzbekistan or Georgia; hybrid or remote
Company
delivers enterprise technology projects for global clients across healthcare, manufacturing, e-commerce, fintech, SAP, and web technologies.
What you will do
- Lead and grow a small, high-performing team of data scientists.
- Lead ML initiatives embedded in client product teams, turning complex business problems into shippable models.
- Collaborate with customers and engineering teams to clarify business needs and translate them into technical solutions.
- Participate in presales activities by providing technical insights and shaping project proposals.
- Contribute hands-on through coding and individual technical work when needed.
Requirements
- 7+ years of experience in at least one machine learning field.
- 2+ years of experience in a technical leadership role, such as Architect.
- 2+ years of experience managing or supervising teams.
- Familiarity with generative AI, time series forecasting, natural language processing, and computer vision.
- Ability to lead meetings, clarify requirements, and explain technical trade-offs confidently.
- English at B2+ level required.
Culture & Benefits
- Projects span startups, enterprise solutions, research and development, SAP, and modern web technologies.
- Global clients include European and US-based organizations, including Fortune 500 companies.
- Employment is with rather than a single project, with opportunities to move to a new project when one ends.
- Market-based compensation and regular performance reviews.
- Internal expert communities, courses, and perks supporting professional growth and well-being.
- Average employee tenure is more than four years.
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