Data Scientist, Delivery

fulltime
Expired

Employment Information

The position you were interested in has been filled or expired, but we invite you to explore other exciting job openings on our platform to find your next career opportunity.

About us

With over 150 million customers in 45+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people. Everyone's welcome at Bolt, regardless of race, colour, religion, sex, national origin, age, disability, sexual orientation, or gender identity. We’re on a mission to make cities for people, not cars, and we need you to make it happen!

About the role

You will be building models to estimate the food preparation time at various stages of the order, such as before and after the order has been accepted. You will also be developing complex demand forecasting pipelines for our Bolt Market dark stores. You will be involved in creating simulations to understand the impact of varying market conditions on our business metrics.

Your daily adventures will include:

  • Working with a technical stack consisting of Python, Docker, SageMaker, Airflow, Spark, Presto
  • Solving real world problems using gradient boosted trees, mathematical optimisation, time series forecasting, recommender systems, deep learning and more
  • Understanding the core needs of our Delivery businesses and translating their problems to technical specifications
  • Handling the entire lifecycle from exploratory queries and notebook prototypes to a working machine learning model or other automation that might be serving thousands of calls per second in production
  • Leveraging our in-house model lifecycle platform that allow you to launch new projects in a matter of days
  • Working in product feature teams together with data analysts, product managers and software engineers
  • Discussing the problems and technical innovations within the broader data science team that provides a pool of peers and mentors
  • Deploy and validate solutions for millions of users, enabling fast feedback and measurable added value to customers
  • Using optimisation techniques for dispatching, demand/supply balancing to minimise the delivery time of our orders
  • Building recommender systems and rankers to provide the best ordering experience to our clients

About you:

  • Industry experience in data science and machine learning (3+ years recommended)
  • Awareness of both business and technical aspects of data science
  • Experience in Python programming, including libraries like Pandas, Numpy, sklearn, OR-tools
  • Understanding and practical experience with statistical hypothesis testing
  • Proactive mindset, willingness to take initiative and work with little supervision
  • Hands-on experience with most used methods for dimensionality reduction, clustering algorithms, rankers, regressors, classifiers, etc (PCA, DBSCAN, Spectral Clustering, gradient boosted trees, deep neural networks, SVM, linear/logistic regression, ranking models and others)
  • Enthusiasm to collaborate with different roles in product, analytics and engineering to identify problems, explore trends and discover growth opportunities
  • Strong verbal and written communication skills in English
  • Track record of deploying models to production and measuring the impact
  • You will get extra credits for product development experience in a technology company

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying if you feel you’re the kind of person described above!

Why you’ll love it here:

  • Play a direct role in shaping the future of mobility.
  • Impact millions of customers and partners in 500+ cities across 45 countries.
  • Work in fast-moving autonomous teams with some of the smartest people in the world.
  • Accelerate your professional growth with unique career opportunities.
  • Get a rewarding salary and stock option package that lets you focus on doing your best work.
  • Enjoy the flexibility of working in a hybrid mode.
  • Take care of your physical and mental health with our wellness perks.

*Some perks may differ depending on your location.

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