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Lead Data Science Engineer
Up Labs
WorldwideRemote2w ago
- Employment
- Full-time
- Seniority
- Lead
About the role
- Act as the primary owner of Data Science, Analytics, and Data Engineering as a subject matter expert
- Build out a team and incubate expertise amongst several venture start-ups
- Create rapid proofs of concept, then scale into functional MVPs to turn concepts into tangible reality.
- Mentor and support early-stage venture teams to achieve bigger outcomes at a greater scale in data density and system complexity.
- Cross-pollinate learnings, best practices, and insights between multiple ventures to drive continuous improvement of Engineering and Data Science at UP.Labs.
- Enjoy working in a diverse, dynamic, collaborative, transparent, and inclusive environment where all ideas and opinions are equally valued
- 8 years experience within Data Science, Data Engineering, and Machine Learning domains and their practical applications
- Experience working in a startup environment; member of a founding team ideal.
- Hands-on experience with machine learning algorithms like random forest, linear and logistic regressions, gradient boosting, classification, algorithms for building, evaluating, deploying and monitoring ML models from scratch.
- Familiarity and preference for working in ambiguous, fast-paced environments such as startups and growth-phase tech companies.
- Hands-on and end-to-end product build, development, and delivery experience.
- Experience working with or managing and leading remote, distributed teams including full-time data scientists, engineers and vendors/contractors.
- Awareness of the latest in Data Science and Data Engineering trends, as well as new use cases within the ML Space.
- Experience working with major cloud environments (Azure, GCP, AWS) and cloud-native software architectures.
- Experience with Database and Warehouse solutions, e.g. Data Bricks, Snowflake, Fivetran, DBT and respective public cloud data infrastructure service offerings from AWS, GCP, and Azure.
- Strong experience in collaborating with Product teams to find effective solutions.
- Strong communication skills put to use by explaining technical vision and deeply technical concepts to a variety of multidisciplinary team members.
- An open, curious, and humble mindset that builds on to our open, inclusive, and collaborative environment.
- Experience with systems planning in the domains of transportation, aviation, or digital simulation would be valuable.
- Containerized deployment Tools like Kubernetes, and Docker
- Infrastructure as Code Tools like Terraform and OpenTofu
- Familiarity with AB testing setup and analysis
- Familiar with Reinforcement Learning for practical use cases
Perks & benefits
- Distributed Team
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