Data Science Engineer - Startup

Why should you join us :

- Work in an exciting start-up that builds first-of-its-kind product and services

- Have access to a unique dataset covering - 85% of SMEs with unmatched diversity and complexity

- Have the opportunity to build truly state-of-the-art algorithms and insight engines that consume and digest complex

- Big data and extract value out of them

- Learn and get exposure to multiple engineering areas (including Big Data technologies, DevOps) surrounded by a top-quality team

- Accelerate your career in a fast-paced, open, non-hierarchical working environment

The Team :

The Data Scientists team builds the algorithms and insight engines that sit at the core of the company's value proposition.

- This is a team of intellectuals with high aptitude, hacker attitude, strong curiosity about data, great comfort with Math, good coding discipline and excellent communication skills.

What will you be doing :

- Build tools to ingest new data and persist it into a database

- Build tools / wrappers to easily query, select & download the desired data slice to a local machine from the Big-Data storage DBs, in a tabular format (e.g a CSV file)

- Port the algorithms developed by data scientists into the Big-Data framework so that they can be executed at scale within the constraints of the production environment

Who are we looking for :

- Very strong coding skills in any one of Python/R/Scala

- Strong in Data Structure/Algorithms especially Data Algorithms

- Experienced with using distributed data processing layers like Spark, Map Reduce, Akka. (must be strong in at least one of these)

- Experienced with using distributed persistence systems like NoSQL, Cassandra, Hadoop, S3. (must be strong in at least one of these)

- Sound understanding of statistics and linear algebra

- Basic Knowledge of machine learning concepts

- 3 to 7 years in technology industry with Post Graduate Degree in Mathematics / Statistics / Engineering

- Prior experience with start-up environment preferred