Machine Learning Engineer
4 weeks ago
Job Description :
About the Digital Business Unit at IndusInd:
The mandate of the Digital Business Unit at IndusInd Bank is as follows :
- Building customer centric products with human centered design principles for retail Individual and micro, small and medium enterprise (MSME) customer segments
- Build innovative products and propositions backed with problem solving mindset to discover and solve latent needs of customers
- Build Embedded Finance (Banking as a Service) applications
- Ensure designs are highly available, highly modular, highly scalable and highly secure
- Drive digital business
Some of the applications managed by the Digital Business Unit include IndusMobile (bank's mobile app for retail individual clients), Indusnet (net banking application of the bank), IndusMerchantSolutions app, Whatsapp Banking, Chatbots, easycredit for Individuals, easycredit for Business Owners, savings, current account and fixed deposit online platforms. There are many more innovative digital products and solutions in pipeline.
The unit's objectives are three fold - (a) Drive better customer experience and engagement (b) transform existing lines of businesses and (c) build new digital only or banking as a service led digital business models
About the Role :
We are looking for a highly capable machine learning engineer to optimize our machine learning systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.
Job Responsibilities :
Mandatory Skills :
- 2+ years of experience in data analysis and data manipulation
- Knowledge of cloud environments (data bricks, aws, azure etc.) for data handling and analysis is mandatory
Coding requirements :
Hand-on work experience on advance level of python, SQL, big data interfaces - pyspark, hadoop etc.
Other required skills :
- Develop and implement machine learning algorithms and models to solve complex business problem
- Collaborate with data scientists, software engineers, and business stakeholders to identify opportunities to apply machine learning to improve business outcomes
- Design, develop, and implement end-to-end machine learning systems, including data pre-processing, feature engineering, model training and evaluation, and deployment
- Create and own cloud native API to deploy ML Models
- Participate in code and design reviews, and contribute to the development of best practices and standards for the machine learning team
- Automate campaigns in a scalable manner to optimize compute and infrastructure cost
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field
- 2+ years of experience in machine learning, data science, or a related field
- Strong programming skills in Python and experience with popular machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
- Pyspark experience is a plus
- Experience with data pre-processing, feature engineering, model selection, and evaluation
- Experience with cloud platforms and their AI/ML offerings
- Strong understanding of statistical concepts and their applications in machine learning
- Excellent written and verbal communication skills, with the ability to effectively communicate technical concepts to non- technical stakeholders
- Financial industry experience is a plus
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