Senior Quantitative Analytics Specialist
The Wells Fargo Foundation
Location
Bangalore | India
Job description
About this role:
Wells Fargo is seeking a Senior Quantitative Analytics Specialist...
Senior Quantitative Analytics Specialist is a partner-facing role and is responsible for delivering high impact analytic and data science projects by using analytics and AI.
Primary role of the advanced analytics consultant in the Consumer Modeling COE is to apply business knowledge and advanced programming skills and analytics to serve as a subject matter expert, analyst, advisor and consultant to support model lifecycle - model development, performance testing, data analysis, model implementation, model production, delivery of model results, change management, documentation and governance.
Responsibilities - Required to work individually or as part of a team on multiple data science projects and work closely with business partners across the organization. Mentor and coach budding Data Scientist on developing and implementing data science solutions.
- Perform various complex activities related to statistical/machine learning. Provide analytical support for developing, evaluating, implementing, monitoring and executing models across business verticals using emerging technologies including but not limited to Python, Spark, and H2O etc.
- Expert knowledge on working on large datasets using SQL and present conclusions to key stakeholders.
- Establish a consistent and collaborative framework with the business and act as a primary point of contact in delivering the solutions.
- Experience in building quick prototypes to check feasibility and value to business.
- Expert in developing and maintaining modular code-base for reusability
- Review and validate models and help improve the performance of the model under the preview of the banking regulations.
- Work closely with technology teams to deploy the models to production.
- Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements
Essential Skills
- Bachelors or Masters degree in Engineering field like computer science, Information technology, Electrical Engineering etc.
- M.Sc./M.Phil. in statistics/ economics/ mathematics/ operations research engineering physics
- 5 - 8 years of relevant hands on experience in data science and advanced analytics.
- Must have hands on exposure in Python, PySpark and SQL.
- Expert knowledge of libraries like sckit-learn, pandas, numpy, mllib, matplotlib, keras…
- Expert in data mining and statistical analysis.
- Experience in developing, implementing models.
- Statistical models - linear regression, logistic regression, time series analysis, multivariate statistical analysis
- Machine learning models - Random forest, XGBoost, GBM, SVM…
- Exposure to deep learning framework - ANN,RNN, CNN, LSTM
- Excellent understanding of model metrics including AUC, ROC, F-statistics etc. with clear understanding of how model performance is tuned
- Strong programing skills.
- Hands on knowledge in one or more of Big Data skills - SQL, Aster, Teradata, Hadoop, SPARK, H20, BigQuery.
- Exposure to Google Cloud Platform
- Critical thinking and strong problem solving skills
- Ability to learn the business aspects quickly
- Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.is desirable
- Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry is desirable
- Ability to multi-task and prioritize between projects
- Ability to work independently and as part of a team
Desired Skills
- Working expertise in Tensorflow, Keras or Pytorch would be added advantage
- Working knowledge in developing end to end ML/AI pipeline in Apache Spark, Sparkling Waters, H2O, Caffe in Hortonworks/Cloudera and/or MapR or Teradata Aster big data platforms
- Ability to work with Data Engineers in discovering and optimizing bottlenecks in the AI/ML pipeline for real-time or near-real-time applications that consumes large throughput of data
Posting End Date:
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Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
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