I'm currently building a team of experienced data scientists to handle all my data science projects. Customers range from retail/e-commerce/travel, insurance, finance/trading/investment, hotel, telcos, banking.
We use a Python stack, together with big data infra (Kafka, Cassandra, Spark/Hadoop). We're looking for data scientists who can write code - not those who use client side tools like SAS, Rapidminer, Weka, etc.
Typical predictions are:
(1) customer spend over (next 6 months)
(2) product / product category purchase propensity (next 6 months)
(3) likelihood of churn
(4) cross-sell / up-sell targeting
(5) pricing optimization
(6) risk modelling / fraud detection
We're looking for people who can commit at least 30hrs a week (min. 5 hours daily), so do ensure you have time before applying.
Only responsible and experienced people need apply.
We're looking for A players.
We're looking for people who stay committed once they say they do.
We're looking for long term partners.
**I have detailed my strategy in the Interview.zip (attached here). As part of the interview, pls review it and let me know how you would better improve the current solution. Pls be as detailed as possible because it will allow me to know your depth of expertise. Through your detailed explanation, I can tell how experienced you really are.**
In order for me to pick you, you should provide sufficiently detailed description of how you would tackle the problem, and why. Don't tell me things that I can already find on Google or Scikit-Learn Guides. :)
This team will handle all data science projects we bring in. We have about 3-5 new customers every month so we're looking for serious people with serious capacity.
2 projects on the most immediate term:
- Developing the core automated customer predictive modelling infrastructure / algorithm / evaluation on www.conclude.io
- Developing a trading prediction model using fundamental analysis and news (text) analysis (working with a hedge fund focused on FX with 2500% returns over 20 years)