ROLE

Senior Data Scientist

Who we are.
A greenfield startup looking to disrupt e-commerce by using data and technology to help brands deliver the best pricing to their customers no matter what. The company is founded and backed by a team of successful entrepreneurs with several successful exits, looking to make this their next.
01

What we are
looking for.

We are looking for an entrepreneurial and business minded Senior Data Scientist to help us disrupt the e-commerce industry. We believe it is time for technology and data to help Merchants deliver the best pricing to their customers, no matter what. If you are looking for an opportunity to join a start-up led by a proven founder in an industry that is growing exponentially and an opportunity to work alongside a small and focused Machine Learning Engineering team, then this is the opportunity to work on something not only exciting and fun, but also creative in ways that most people will never experience in their lifetime.

02

What you will do.

You will work side by side with e-commerce experts and leads in the design and development of machine learning models to deliver optimal pricing for merchants. You will be responsible for determining and capturing features best suited to achieve accurate predictions around dynamic pricing and demand forecasting.

In this role, you will build and validate machine learning models, research relevant statistical methods, improve and optimize code, perform data analysis, and putting machine learning models into production.

03

Who you are.

You are passionate about statistics, mathematics, software engineering and machine Learning. You are pragmatic and effective, looking for all possible ways of improving your models. You attack complex business questions with data and curiosity, diving below the surface to identify the root cause.

You have a deep understanding of the different parts of the data pipeline, having been exposed to data engineering, data analysis, data science and machine learning engineering. You thrive working in a “get it done” and fast-paced start-up environment, which requires high effectiveness and efficiency. You always deliver quality work, but you embrace failure as a way to improve!

A successful candidate must:

  • Be able to understand the business needs first and then apply technology to solve those problems.
  • Have strong analytical and data visualization skills, to be able to conduct and present to stakeholders an advanced Exploratory Data Analysis.
  • Have strong experience in feature engineering and machine learning modelling
  • Be able to improve predictive performance by applying statistical and mathematical techniques when faced with limited data.
  • Have excellent communication and organization skills both towards the leadership and the data team.
  • Be able to work autonomously and have the ability to come up with innovative ideas on their own.
  • Be passionate about solving real world problems using machine learning and data science and have a keen interest in computer science and software engineering.

04

Requirements

  • At least 3 years working professionally in the machine learning and data science field.
  • At least a master’s degree in computer science, mathematics, statistics, physics, data science, machine learning or related field.
  • Proven experience as an ML engineer or data scientist building and developing deep learning models and other key machine learning algorithms.
  • Proven experience in taking machine learning algorithms from R&D to production, using cloud technologies.
  • Proficiency in Python and at least some experience in other programming languages (e.g., Java and other object-oriented languages).
  • Have some experience with dynamic pricing or sales/demand forecasting or similar.
  • Having experience in dynamic programming, operations research and/or reinforcement learning will be a big plus
05

Good to have

sample

To apply, please send us a brief paragraph about why you are interested. Please share with us examples of your proudest projects on Kaggle or Github or open source contributions.

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