11/05 Grishma Udani
Product Manager at CommonFloor

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CommonFloor - Data Scientist/Machine Learning (3-10 yrs)

Bangalore Job Code: 64288

Are you an inherently curious thinker who loves challenges- Do you enjoy deep diving into data to find answers to yet unknown questions- Are you the restless kind who needs a difficult problem to keep them occupied at all times- But at the same time, do you have the patience to chase the unknown in massive data sets which will invariably take up lot of time and involve lot of trial & error- If you answered - yes- to all of the above, we are looking for you!

We are commonfloor, India's fastest growing real estate website. Backed by likes of Accel, Tiger & Google capital, we are on a mission to - to bring the real estate ecosystem on digital - common floor- by bringing transparency in Real Estate using technology- . And we strongly believe data intelligence is one of the most critical pieces of the puzzle. To this end, we are building a machine learning team in our newly formed innovation arm, CF exponent. You- ll be working in a startup within a startup tackling some of the hardest data science problems in Real Estate and influencing our users- biggest purchase of his/her life (their dream home).


- Translate unstructured business problems into abstract mathematical frameworks.

- Research & develop scalable machine learning algorithms using large amounts of high-dimensional data.

- Productize proven or working models into production quality code. Build and maintain scalable data warehouse infrastructure

- Stay current with latest research & technology ideas - apply new methodologies in the intersection of applied math / probability / statistics / computer science to ensure an edge in data intelligence.

- Partner with Product and Business teams to identify trends, new products, and opportunities.


- Bachelors or Masters in Computer Science/Math/Applied Math/Statistics or related fields preferably from one of the premier institutes.

- Experience: We are looking for people at all levels of experience but we measure experience more from amount of interesting stuff done relative to years rather than absolute years.

- Any prior experience in machine learning, artificial intelligence, natural language processing is a huge plus.

- Passion for applied math. Strong intuition for data and Keen aptitude on large scale data analysis.

- Must have knowledge/experience is some/all of these: regression analysis, predictive models, Bayesian classification, collaborative filtering, decision trees, and common clustering algorithms.

- Familiarity with distributed systems and methodologies, Data Wrangling: Hadoop, MapReduce, Cascading, Hive, Pig, Elastic Map-Reduce etc.

- Experience with some of NoSQL/graph databases: Neo4J, MongoDB, Riak, Cassandra

- Strong SQL skills and experience/knowledge of massive relational database system.

- Familiarity with at least one compiled language (e.g., Java, C++) and one dynamic scripting language (e.g., Ruby, Python, Perl)

- Familiarity with a modeling language (e.g., Mathematica, Matlab, R).

- Experience with cloud technologies: AWS, Rackspace (PLUS)

- Comfortable working on any part of the stack.

- Good people skills, great communication skills. The ability to explain what you do in plain english to relevant stakeholders is a huge plus.

- Ability to work in a startup, meaning: Ability to work unsupervised, take responsibility, go beyond your formal job responsibilities & do whatever it takes to get the job done.

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