Client oriented approach to problem solving. Individual should be able to have a holistic view of multiple businesses and develop analytic solutions accordingly.
Own and deliver multiple and complex analytic projects. This would require an understanding of business context, conversion of business problems in modeling, and implementing such solutions to create business value.
Always up to date with the latest use cases of modeling community, machine learning and deep learning algorithms and share knowledge within the team.
Proficiency in basic statistics, hypothesis testing, segmentation and predictive modeling.
Ability to translate and articulate technical thoughts and ideas to a larger audience including influencing skills with peers and senior management.
Strong project management skills.
Ability to coach and mentor juniors.
Eagerness to work on new and challenging tasks on a regular basis with an ability to research new ways of doing things better/efficiently.
Contribute to organizational initiatives in wide ranging areas including competency development, training, organizational building activities etc.
Basic Qualifications –
Bachelor’s Degree with 3+ years of experience in data analytics,
Hands-on experience in Python / SAS or R programing along with strong experience in SQL and Excel Macros.
Experienced in working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and coding.
Well versed with necessary data preprocessing and feature engineering skills.
At least 2 years of experience implementing Machine learning algorithms such as Random Forest and Gradient Boosting in solving business problems such as Default classification and macroeconomic forecasting.
At least 1 year of experience implementing deep learning techniques like neural networks
Exposure to deep learning packages like Tensorflow
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