Data Scientist Role

4 days ago


Lahore, Punjab, Pakistan Tajir Full time
About Tajir

Tajir is a revolutionary e-commerce platform that aims to make a significant portion of Pakistan's economy more efficient. We strive to disrupt the traditional retail industry by offering an app where stores can buy everything they need, delivered reliably the next day.

Our mission is to drastically reduce the number of vehicles on the road with efficient, centralized delivery, resulting in higher profits for both store owners and manufacturers. With massive purchasing power, even modest efficiency gains have an outsized economic impact.

We are backed by prominent investors like Kleiner Perkins and Y Combinator, early backers of notable tech giants such as Google, Amazon, Coinbase, Airbnb, and Dropbox. Learn more about us on Forbes and Geo News.

What You'll Do

As a key member of our team, you will leverage real-time data on customer preferences to provide an unrivaled experience to our customers. Our Data Scientists design algorithms to support our operation, from purchase orders all the way to delivery. These algorithms are tested on real and simulated data.

You will be responsible for finding answers in data by identifying common features of our strongest customers, what products are bought together, and areas where our delivery operation is weakest. Your role involves answering novel questions by diving head-first into data.

Your primary goal is to enable data-driven decisions by facilitating rapid answers to all data queries. If it takes a week to answer a data question, poor decisions may be made using instinct and superstitions.

Requirements
  1. You must have >2 years of experience as a Data Scientist.
  2. Elite SQL querying skills are essential, including complex joins, CTEs, LIMIT, OFFSET, GROUP BY, HAVING, and obscure querying features.
  3. Experience with non-querying parts of SQL, such as DDL, procedures, and indexes, is also required.
  4. You should be proficient in Python, including the pandas and numpy libraries.
  5. An understanding of relational databases (e.g., Postgres) versus columnar databases (e.g., BigQuery) is necessary.


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