Data Scientist

7 days ago

Bengaluru Karnataka, India PradeepIT Consulting Services Full time

**About the job Data Scientist**:
Education and Work Experience Requirements:

- 5 to 9 years of experience as Data Scientist
- Proven track record and experience with statistical modeling/data mining algorithms such as
- Multivariate Regression, Logistic Regression, clustering algorithms, Support Vector Machines,

Decision Trees etc
- Machine learning, deep learning, graph mining.
- DOE, Forecasting, Segmentation, Uncertainty Analysis etc.
- Data Mining i.e. Text Mining, Classification Methods SVM, NN, etc
- Vector Space model for Unstructured Text
- Sentiment Analysis, Association Mining, Semantic Analysis
- Good knowledge of advanced statistical methods. Experience working with Text Data using

transformer-based model
- Experience in creating statistical models and/or optimization frameworks for improving

processes/products/profits
- Expertise with one of the following scripting languages:

- Python, R, Tensorflow, Keras, Pytorch
- Scikit-learn, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs

un-supervised tasks.
- Tech savy and willing to work with open-Source Tools
- Good to have foundational knowledge on Cloud, API frameworks like Flask, Fast API
- Prior experience working on Mobility or Healthcare domain will be a plus

Mandatory Skills:

- Develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong

focus on language models.

methods as necessary, pertaining to customers discovery, and viewing experiences to identify

critical product insights.
- Experience in creating statistical models and/or optimization frameworks for improving

processes/products/profits
- Interact with our research team and with key partners in the market to build end-to-end AI/ML

solutions: Conversational AI, document understanding

discovery, and viewing experiences to identify critical product insights.
- Drive efforts to enable product and engineering leaders to share your knowledge and insights

through clear and concise communication, education, and data visualization.
- Translate analytic insights into concrete, actionable recommendations for business or product

improvement.
- Build and improve reusable tools & modelling pipelines and support knowledge sharing across

several teams.

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