Data Scientist

7 months ago

Bengaluru Karnataka, India PayU Full time

**Roles and Responsibilities**:

- As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for
- carrying out analytical initiatives which will be as follows:
- Dive into the data and identify patterns
- Development of end-to-end ML models leveraging different type of data sources - Telco, Payments, Social Media etc.
- Working on Big Data to develop analytical solutions
- Collaborate with various stakeholders (e.g. tech, product) to understand and design bestsolutions which can be implemented
- Working on cutting-edge techniques e.g. machine learning and deep learning models

**Requirements to be successful in this role**:

- Degree (BE / B.Tech / MS, PhD or equivalent) in Computer Science, Mathematics, Operational
- Research, Statistics or Natural Sciences
- At least 2 years of work experience on building ML models using telecom datasets
- Strong problem-solving skills with an emphasis on product development.
- Work with and create data architectures.
- A very clear understanding of probability and statistics, analytical approach to problem solving capability to think critically on a diverse array of problems
- Supervised Machine Learning Algorithms: Predictive Analytics, Logistic Regression, Bayesian
- Approach, Decision Trees, Support Vector Machines. Bagging and Boosting algorithms - Random Forest, XGboost, Catboost, Neural Networks etc.
- Understanding of advanced algorithms (i.e. Deep Learning, Probabilistic Graph Models) will be good to have
- Familiarity with statistical methods such as hypothesis testing, forecasting, time series analysis,etc - gained through work experience or graduate level education
- Experience with relational databases NoSQL databases such as MongoDB, Elastic Search, Redisor any graph database
- Skilled at data visualization and presentation
- Most importantly, an inquisitive mind, an ability for self-learning and abstraction along with a risk appetite for experimentation and failure
- Strong problem solving and understand and execute complex analysis
- Experience in Python, Spark and SQL is a must
- Familiarity with the best practices of Data Science

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