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| Job Location | Pune |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | Banking / Financial Services |
| Functional Area | Finance / Accounts / Tax,Operations Management / Process Analysis |
| EmploymentType | Full-time |
* Duties and Responsibilities - PRINCIPAL ACCOUNTABILITIES (Accountabilities associated with the job) Knowledge and working experience in one or more of the following areas: Natural Language Processing Clustering and Classifications of Text Question Answering Text Mining Information Retrieval Distributional Semantics Knowledge Engineering Search Rank and Recommendation. Deep experience with text-wrangling and pre-processing skills such as document parsing and cleanup vectorization tokenization language modeling phrase detection etc. Proficient programming skills in Python (Libraries Pandas + Numpy) and SQL Programming. Being comfortable with rapid prototyping practices. Being comfortable with developing clean production-ready code. Being comfortable with pre-processing structured unstructured or semi-structured data Experience with statistical data analysis experimental design and hypothesis validation 4. MAJOR CHALLENGES (Challenges faced on an on-going basis in carrying out the job) Ensuring capability delivery working with various support & business functions Understand Data Science Algorithms & Coding complexities (able to translate advanced ML Data Science to live capability) level 5. DECISIONS (Key decisions taken by job holder at his/her end) Implementation approach for scalability Effective ML technical & infrastructure Solution Approach ML model integration approach 6. INTERACTIONS (Key working relationships a job holder needs to have INSIDE and OUTSIDE the company to accomplish the job) Internal Clients Roles you need to interact with inside the organization to enable success in your day to day work Business Teams Internal Operations team IT Team External Clients Roles you need to interact with outside the organization to enable success in your day to day work Large enterprise technology partners ML Partners 7. DIMENSIONS (Key numerical data which will reflect the scope and scale of activities concerning this job) Financial Dimensions (These should be quantifiable numerical amounts) Other Dimensions (Significant volume dimensions associated with the job) Total Team Size: 0 Number of Direct Reports: Number of Indirect Reports: Number of Outsourced employees: Number of locations: Number of products: , * SKILLS AND KNOWLEDGE (Minimum acceptable proficiency for this job which best indicates the education and/or experience requirements of this job and not the incumbent) Educational Qualifications Qualifications Bachelor Degree in Computer Science, Math, Physics, Engineering, or related quantitative field Understanding of statistical analysis, Strong background in python 5+ years of experience building sparse data models: Neural Network / Deep Learning / Bayesian Networks / Monte Carlo Markov Chain / SVM / GBM / Lookalike models / Feature engineering Passionate about extracting value out of data by creating new variables, understanding base variable relationships Work Experience Natural Language Processing (e.g. Spacy, NLTK, OpenNLP or similar) Applied Machine Learning (e.g. Scikit-learn, H2O or similar) Traditional Databases Proficiency in traditional Machine Learning models such as Linear Regression, Logistic Regression, CART, Random Forest, XGBoost, etc. Familiarity with Deep Learning architectures and frameworks such as Pytorch, Tensorflow, Keras.
Keyskills :
bankingfinancefilingmisstatistical data analysisnatural language processingtext miningdata sciencedata analysismachine learningnatural languagelarge enterpriseexternal clientslinear regressionnbfcmonte carlo