Head - Analytics at Experian India Ltd
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Experian - Senior Data Scientist (7-12 yrs)
Essential Duties and Responsibilities
- Problem solver with curious mindset with a high execution bias having relevant work experience in Data Science in retail banking domain.
- Data scientist with hands-on expertise in building and executing analytics modules on various technology platforms including big data technology platforms.
- Successful candidates are intellectually curious builders who are biased toward action, scrappy, and communicative.
- Own and complete work streams from business levers, domain know-how, and bias for execution and delivery.
- Be able to compile results from various work streams and be able to make coherent presentations to internal and external stakeholders.
- Experience in building or managing data products, high performer and problem solver.
- Applying best practices to manage solution implementations including code design and reviews
- Engage Business/Technical Consultants and delivery teams appropriately so that there is a shared understanding and agreement as to deliver the proposed solution
- MS or PhD in Computer Science, Engineering, Mathematics, Statistics or a related field with solid exposure to Machine
- Learning and/or Advanced Analytics with 7+ years of experience in predictive analytics and exposure to big data analytics.
- MBAs with relevant data science skills will also be considered.
- Strong understanding of the financial domain. Desired domain expertise in credit Risk, telecom analytics, retail analytics.
- Strong coding skills in Python is a must, and in other languages like R and SQL, Hive Sql
- Hands-on experience with Python libraries - NumPy, Pandas, sklearn
- Hands-on knowledge of working with scalable platforms for processing large and/or complex multi-source datasets using Hive, Hadoop or Spark (PySpark) is a plus.
- Comfortable with working on Unix, Windows, and databases like Elastic Search and MongoDB
- Demonstrated the use of data optimization (Linear/Non-linear) to solve constrained business problems
Must have experience
- Sound knowledge of machine learning concepts. Illustrative machine learning methodologies are:
- Bagging, Boosting, Regularization, Online Learning, One Hot Encoder etc.
- Statistical modeling - CHAID, CART, Regressions, SVM, SVD etc.
- Experience on the text analytics stack - NLP, NLU, LDA, TF-IDF etc.
- Ability to communicate analytics-based insights to business stakeholders. Independent problem solver comfortable to work in an ambiguous solution space. Strong PPT Skills, Excel
- Demonstrated experience in delivering analytics projects in high-pressure environments