Lead Data Scientist

Job Description: 

As the Lead Data Scientist at UP.Labs, you'll get to play a key and unique role in building new startups from 0 to 1 and creating practical outcomes from emergent technologies and accessible data.

You'll act as the principal domain hands-on expert and owner of data science for a technology venture. You will collaborate with our venture teams to drive both high-level and day-to-day analysis data engineering overview. This includes everything from assisting in validating the initial business concepts, ideating and validating data use cases, developing proof of concepts, and working closely with the product and engineering team members to drive practical outcomes. You’ll have the support you need to drive new innovation in impactful domains ripe for change and growth and be at the forefront of creating a more intelligent industry.

In this role, you will:

●     Act as the primary owner of Data Science, Analytics, and in some cases 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 effective 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

You should have:

●     7+ years experience within Data Science, Data Engineering, and Machine Learning domains and their practical applications

●     Hands on experience with machine learning algorithms like linear and logistic regressions, XGBoost, random forest, and anomaly detection algorithms for building, evaluating, deploying and monitoring ML models from scratch.

●     Familiar with time series analysis, LSTM (and other deep learning approaches for sequence analysis)

●     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 agile, lean, and Continuous Delivery approaches, such as Continuous Integration, TDD, Infrastructure as Code, etc

●     Experience working with major cloud environments (Azure, GCP, AWS) and cloud-native software architectures.

●     Experience with Databases, Data Warehousing, and ETL systems and solutions, e.g. Oracle, Data Bicks, Snowflake, and respective public cloud 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.

Additional desired competencies:

●     Experience with systems planning in the domains of transportation, aviation, or digital simulation would be valuable.

●     Familiarity with the concepts of dynamic and continuous pricing, assortment optimization as applicable to the air