Job Description: Mid-Senior Data Scientist

As the 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 hands-on expert and owner of data science for a technology venture. You will collaborate with our venture teams to drive day-to-day data science efforts. 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.

In this role, you will:

●     Act as the owner of Data Science, Analytics, and in some cases Data Engineering as a subject matter expert

●     Create rapid proofs of concept, then scale into functional MVPs to turn concepts into tangible reality.

●     Mentor and support the team members to achieve bigger outcomes at a greater scale in data density and system complexity.

●     Enjoy working in a diverse, dynamic, collaborative, transparent, and inclusive environment where all ideas and opinions are equally valued

You should have:

●    (focus) MSc or PhD in a quantitative field (Statistics, Math, Economics, or Data Science preferred) with 4-7 years experience within Data Science and Machine Learning domains and their practical applications

●     (focus) Hands on experience with classic optimization and machine learning algorithms: regressions, operations research, constraint optimization, integer programming, intervention analysis, xgboost, lgbm, random forest, and anomaly detection algorithms for building, evaluating, deploying and monitoring ML models from scratch.

●     (focus) Experience with filtering and cleansing unstructured (or ambiguous) data into usable data sets that can be analyzed to extract insights and used for feature engineering.

●     (focus) Hands-on and end-to-end product build, development, and delivery experience.

●     (focus) Ability to clearly explain technical concepts in English

●     Experience with Databases, Data Warehousing, and ETL systems and solutions, e.g. Oracle, DataBricks, and respective public cloud service offerings from AWS, GCP, and Azure.

●   Familiarity with time series analysis, LSTM (deep learning approaches for sequence analysis are a plus)

●     Familiarity and preference for working in ambiguous, fast-paced environments such as startups and growth-phase tech companies.

●     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 in collaborating with Product teams to find effective solutions.

●     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.

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

●     Knowledge of Bayesian models, Monte Carlo simulations and survival methods are beneficial

●     Familiarity with AB testing setup and analysis

●     Familiar with Reinforcement for practical use cases

UP.Labs Summary:

We build high-growth technology startups that enable faster, cleaner, and safer movement of people and goods. Our vision is to transform the moving world by pairing leading corporations and entrepreneurs with a proven methodology for launching and scaling software and hardware companies.