Ideal candidate must have:

<ul>
<li style="margin-left:0px;">Advanced understanding of statistical analysis, ability to apply analytics in all aspects of the business risk and fraud, growth, collections etc</li>
</ul>

<ul>
<li style="margin-left:0px;">Credit risk modelling for underwriting and portfolio monitoring using traditional and alternate data sources.</li>
</ul>

<ul>
<li style="margin-left:0px;">Preferred experience in banking, payments, B2B/B2C Lending space (unsecured loans or credit card)</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience with large data sets and distributed computing (Redshift/Postgres/Spark) a plus</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience with building insights using varied/alternate data sources</li>
</ul>

<ul>
<li style="margin-left:0px;">Actively collaborate with technology team, product management, operations teams and other stake holders.</li>
</ul>

<ul>
<li style="margin-left:0px;">Move seamlessly between business problems and coding.</li>
</ul>

<ul>
<li style="margin-left:0px;">Present complicated analytical solutions to a non-technical audience</li>
</ul>

<ul>
<li style="margin-left:0px;">Work with very large data sets residing in different data stores in disparate format</li>
</ul>

<ul>
<li style="margin-left:0px;">Readiness to work in a highly results-oriented and fast changing landscape in a fintech start-up Qualification:</li>
</ul>

<ul>
<li style="margin-left:0px;">BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical field.</li>
</ul>

<ul>
<li style="margin-left:0px;">Advanced degrees preferred.</li>
</ul>

<ul>
<li style="margin-left:0px;">1+ years of relevant experience in Banking / NBFC domain.</li>
</ul>

<ul>
<li style="margin-left:0px;">Technical skills required:</li>
</ul>

<ul>
<li style="margin-left:0px;">Fluency with R, Python, and commonly used machine learning frameworks.</li>
</ul>

<ul>
<li style="margin-left:0px;">Build key data sets to empower insights, Spark, SQL, MySQL, SAS, and distributed computing.</li>
</ul>

<ul>
<li style="margin-left:0px;">Proficient in classical ML algorithms (Linear/Logistic Regression, Decision Trees, Boosting, Clustering etc.); Deep Learning/NLP good to have </li>
</ul>

Data Scientist

Ideal candidate must have: Advanced understanding of statistical analysis, ability to apply analytics in all aspects of the business risk and fraud, growth, collections etc Credit risk modelling for underwriting and portfolio monitoring using traditional and alternate data sources. Preferred experience in banking, payments, B2B/B2C Lending space (unsecured loans or credit card) Experience with large data sets and distributed computing (Redshift/Postgres/Spark) a plus Experience with building insights using varied/alternate data sources Actively collaborate with technology team, product management, operations teams and other stake holders. Move seamlessly between business problems and coding. Present complicated analytical solutions to a non-technical audience Work with very large data sets residing in different data stores in disparate format Readiness to work in a highly results-oriented and fast changing landscape in a fintech start-up Qualification: BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical field. Advanced degrees preferred. 1+ years of relevant experience in Banking / NBFC domain. Technical skills required: Fluency with R, Python, and commonly used machine learning frameworks. Build key data sets to empower insights, Spark, SQL, MySQL, SAS, and distributed computing. Proficient in classical ML algorithms (Linear/Logistic Regression, Decision Trees, Boosting, Clustering etc.); Deep Learning/NLP good to have

Data Scientist in Gurugram (UID-16339)

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