Data Scientist

Lendingkart Group; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Lendingkart Group in Bengaluru seeks a data scientist to advance credit analytics and product growth. You will manipulate datasets, build models, and collaborate with product and tech teams.

The role requires 4.5–8 years in statistics or quantitative fields, proficiency in Python, PySpark, SQL, and experience with ML methods and big data tools.

Qualifications

• Bachelor's/Master's/PhD in statistics, mathematics, computer science or a quantitative field.
• 4.5–8 years' experience with data sets and statistical modeling.
• Strong problem-solving and cross-team communication skills.
• Proficiency in Python, PySpark and SQL; knowledge of ML methods.

Skills

Data manipulation

Statistical modeling

Problem solving

Communication

Education

Bachelor's/Master's/PhD in statistics, mathematics, computer science or quantitative field

Tools

Python

PySpark

SQL

NumPy

Pandas

Scikit-learn

TensorFlow

Keras

Tableau

MongoDB

HBase

Spark

Hadoop

AWS S3

SageMaker

Databricks

Job description

Requirements:

• We're looking for someone with 4.5-8 years of experience manipulating data sets and building statistical models, with a bachelor's/master's/PhD degree in statistics, mathematics, computer science, or another quantitative field, from any of the top-tier colleges.


• Strong problem-solving skills with an emphasis on product development.


• Excellent written and verbal communication skills for coordinating across teams.


• Good applied statistics skills such as distributions, statistical testing, and regression.


• Good scripting and programming skills in Python, PySpark, and SQL.


• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, XGBoost, decision forests, artificial neural networks, and their real-world advantages or drawbacks. Knowledge of deep learning techniques is a plus.


• Experience with common data science toolkits such as NumPy, Pandas, Scikit-learn, TensorFlow, Keras, etc.


• Experience with data visualization tools such as Tableau.


• Experience in credit, risk, or collections management (e. g., Application Scorecard, Behavior Scorecard, Collection Scorecard, Loan Pricing, Propensity Model, Cross-Sell Model) is a strong plus.


• Experience with NoSQL databases such as MongoDB, Cassandra, and HBase is desired.


• Experience with distributed data/computing tools like Map/Reduce, Hadoop, Hive, and Spark is a big plus.


• Hands-on experience with cloud computing and big data platforms (e. g., AWS S3, SageMaker, Athena, and Databricks) would be preferred.