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10/10 Vaseeya Nousheen
HR at OLA Cabs

Views:3226 Applications:96 Rec. Actions:Recruiter Actions:11

OlaCabs - Data Scientist - Ola Financial Services (8-12 yrs)

Bangalore Job Code: 752396

Are you this person ?

Are you someone who understands the intricacies of balancing the art and science of applying machine learning and business analytics to consumer lending? Do you itch for putting to use your skills developed in a conventional banking environment into a dynamic, fast paced innovative lending platform that is ahead of the curve? Did the dilemma of start-up atmosphere and a cushy support of funding and brand stump you to choose the right place that gets the best of both worlds? If the answer to all these is not just yes but - hell, yeah!-, then come join us in this incredibly exciting journey as part of the Ola Financial Services group.

Okay, I- m curious. But what is this going to be about (aka Role):

This is a Principal Data Scientist role for a fintech involved in building credit practice in India on mobile platform that envisions to provide convenience, accessibility, transparency and value proposition at one place. Ideal candidate is expected to define, design and deliver solutions using business analytics in a fast paced, next generation banking environment. The reporting line is to Head, Risk Analytics.

Job Roles and Responsibilities - 

- BTech/Masters with 8+ years of relevant experience, Credit Risk, Operations Research, Applied Mathematics/Statistics/Econometrics, Electrical or Systems Engineering, Physics or similarly highly quantitative field.

- Ability to transform business requirements into data science formulations and implement the solutions in an efficient and scalable fashion.

- Excellent interpersonal and stakeholder management skills.

- Ability to handle multiple projects as an individual contributor and/or as a mentor to team members.

- Proficient in R, Python, Scala, Java or similar languages.

- Extensive experience in building production quality models using state-of-the-art. technologies (for eg, tensorflow, scikit-learn, spark).

- Highly analytical with past history of handling teams and engaging business stakeholders.

- Guide the back end infrastructure development and liaison with the engineering team for deployment of models, integration of data.

- Define creative solutions to business problems using advanced mathematical algorithms.

Some insights into our data-science projects:

- Customer profiling using WIFI and geohash data.

- Predict high risk zones using geo-spatial data.

- Identify users home address using geohash data.

- Offer Recommendation Engine/ Market mix models.

- Predict user behavior using human mobility network, social network.

- Predict customers behavior based on their app usage, phone's footprint data.

- And many more to come.

Women-friendly workplace:

Maternity and Paternity Benefits

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