The Senior Data Scientist will design and develop scalable AI/ML solutions, leveraging machine learning, NLP, and deep learning techniques. Responsibilities include feature engineering, exploratory data analysis, data visualization, and deploying solutions in cloud environments. The ideal candidate will have experience with various Python libraries and relational databases while promoting good development practices within the team.
- Design & develop AI/ML solutions to be flexible, scalable & extensible.
- Build solutions that incorporates cognitive techniques such as statistics, machine leaning, NLP, deep learning, transfer learning
- Hands-on in python libraries like pandas, numpy, scikit-learn, scipy, nltk, tensorflow, keras, pytorch etc.
- Excellent at feature engineering, Exploratory data analysis and data visualization
- Keen to work on cloud-based ML solutions using AWS,GCP,Azure,IBM Watson etc.
- Innovative, studies research papers and implement them. Curious to learn latest algorithms and concept and use them professionally
- Develop areas of continuous and automated deployment
- Introduce and follow good development practices, innovative frameworks and technology solutions that help business move faster
- Be a Role Model to the team to collaborate on good object-oriented designs & domain modeling.
- 3-5 years of experience in data science, machine learning field
- An advanced degree in engineering, computer science, statistics or related field is preferred
- Expertise with data science and python, machine learning, NLP and deep learning is essential
- Experience with back-end XML, relational databases (e.g. MS SQL, Postgres)
- Experience developing and deploying solutions using services in the Amazon AWS ecosystem (Serverless Lambda, EC2, RDS)
- Experience of publishing the research paper in renowned forums
Morningstar is an equal opportunity employer.
I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity
Morningstar's hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We've found that we're at our best when we're purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
Top Skills
AWS
Azure
GCP
Ibm Watson
Keras
Ms Sql
Nltk
Numpy
Pandas
Postgres
Python
PyTorch
Scikit-Learn
Scipy
TensorFlow
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