
- Banking Domain
- Assist the team in building Machine learning/AI/Analytics models on open-source stack using Python and the Azure cloud stack.
- Be part of the internal data science team at fragma data - that provides data science consultation to large organizations such as Banks, e-commerce Cos, Social Media companies etc on their scalable AI/ML needs on the cloud and help build POCs, and develop Production ready solutions.
- Candidates will be provided with opportunities for training and professional certifications on the job in these areas - Azure Machine learning services, Microsoft Customer Insights, Spark, Chatbots, DataBricks, NoSQL databases etc.
- Assist the team in conducting AI demos, talks, and workshops occasionally to large audiences of senior stakeholders in the industry.
- Work on large enterprise scale projects end-to-end, involving domain specific projects across banking, finance, ecommerce, social media etc.
- Keen interest to learn new technologies and latest developments and apply them to projects assigned.
| Desired Skills |
- Professional Hands-on coding experience in python for over 1 year for Data scientist, and over 3 years for Sr Data Scientist.
- This is primarily a programming/development-
oriented role - hence strong programming skills in writing object-oriented and modular code in python and experience of pushing projects to production is important. - Strong foundational knowledge and professional experience in
- Machine learning, (Compulsory)
- Deep Learning (Compulsory)
- Strong knowledge of At least One of : Natural Language Processing or Computer Vision or Speech Processing or Business Analytics
- Understanding of Database technologies and SQL. (Compulsory)
- Knowledge of the following Frameworks:
- Scikit-learn (Compulsory)
- Keras/tensorflow/pytorch (At least one of these is Compulsory)
- API development in python for ML models (good to have)
- Excellent communication skills.
- Excellent communication skills are necessary to succeed in this role, as this is a role with high external visibility, and with multiple opportunities to present data science results to a large external audience that will include external VPs, Directors, CXOs etc.
- Hence communication skills will be a key consideration in the selection process.

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