Lead Data Science Engineer

UP.Labs is partnering with a leading construction equipment manufacturer to innovate the industrial sector. The Lead Data Science Engineer will oversee data science initiatives, collaborating with teams to develop and launch impactful AI/ML solutions and data pipelines.

Responsibilities:

• 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

Requirements:

• 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