Principal Data Scientist
Principal Data Scientist
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Job Description
As an expectation a fitting candidate must have/be:
- Ability to analyze business problem and cut through the data challenges.
- Ability to churn the raw corpus and develop a data/ML model to provide business analytics (not just EDA) machine learning based document processing and information retrieval
- Quick to develop the POCs and transform it to high scale production ready code.
- Experience in extracting data through complex unstructured documents using NLP based technologies.
Good to have: Document analysis using Image processing/computer vision and geometric deep learning
Technology Stack:
Python as a primary programming language.
Conceptual understanding of classic ML/DL Algorithms like Regression Support Vectors Decision tree Clustering Random Forest CART Ensemble Neural Networks CNN RNN LSTM etc.
- Programming:
- Must Have: Must be handson with data structures using List tuple dictionary collections iterators Pandas NumPy and Objectoriented programming
- Good to have: Design patterns/System design cython
- ML libraries:
- Must Have: Scikitlearn XGBoost imblearn SciPy Gensim
- Good to have: matplotlib/plotly Lime/sharp
- Data extraction and handling:
- Must Have: DASK/Modin beautifulsoup/scrappy Multiprocessing
- Good to have: Data Augmentation Pyspark Accelerate
- NLP/Text analytics:
- Must Have: Bag of words text ranking algorithm Word2vec language model entity recognition CRF/HMM topic modelling Sequence to Sequence
- Good to have: Machine comprehension translation elastic search
- Deep learning:
- Must Have: TensorFlow/PyTorch Neural nets Sequential models CNN LSTM/GRU/RNN Attention Transformers Residual Networks
- Good to have: Knowledge of optimization Distributed training/computing Language models
- Software peripherals:
- Must Have: REST services SQL/NoSQL UNIX Code versioning
- Good to have: Docker containers data versioning
- Research:
- Must Have: Well verse with latest trends in ML and DL area. Zeal to research and implement cutting areas in AI segment to solve complex problems
- Good to have: Contributed to research papers/patents and it is published on internet in ML and DL
Morningstar is an equal opportunity employer.
Morningstars hybrid work environment gives you the opportunity to work remotely and collaborate inperson each week. Weve found that were at our best when were 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 youll have tools and resources to engage meaningfully with your global colleagues.
I10MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal EntityRequired Experience:
Staff IC
Employment Type
Full-Time
