Simporter 0 — 1-3 роки досвіду EN Advanced Remote
Recruiter
  • Remote
  • Продукт
  • Junior Friendly
  • Startup
  • Back-End
  • Python
  • Python
  • Google Cloud
30.09.22

Про роботу

Simporter is a software that automates new product research for FMCG with AI. We analyze social media, search, reviews, and sales data to recommend new product opportunities for companies like Danone, Calvin Klein, Tommy Hilfiger, and JTI.

We are looking for an experienced Data Engineer to join our team!

This position will be our second hire in Sao Paulo, reporting to and supporting our Lead Forecasting Data Scientist in a small team. This position will cooperate with our Software Engineers and Product Managers, as well.


Responsibilities:

  • Process CPG sales data and extracting additional features to be used for new product sales forecast modeling by a Machine Learning Engineer
  • Work with our Software Engineering team to automate ML Forecast Modeling on a per-company basis, to allow users to forecast sales of new products in real time
  • Automate monthly data & forecast updates in our tool working with external and internal APIs
  • Extract & Identify insights for reporting new product opportunities for Fortune 500 clients


Optionally:

  • Visualize ongoing ML model outputs by working directly with ML Engineering team to empower collaboration between Data Scientists and Product Managers
  • Identify & Scrape data from third party resources such as Google or Twitter to expand our datasets used in ML modeling


Requirement:

  • Previous experience as a data engineer or in a similar role
  • Technical expertise with data models, data mining, and segmentation techniques
  • Knowledge of Python
  • Hands-on experience with SQL database design
  • Great numerical and analytical skills
  • Degree in Computer Science, IT, or similar field; a Master’s is a plus


We offer:

  • Possibility to develop your skills and quickly grow in startup
  • Competitive salary and conditions
  • Team building activities
  • Work in friendly environment


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