Quantitative Analytics Specialist

About this role:

Wells Fargo is seeking a Quantitative Analytics Specialist...

In this role, you will:

• Develop, implement, and calibrate various analytical models.


• Perform highly complex activities related to financial products, business analysis and modeling.


• Perform basic statistical and mathematical models using Python, R, SAS, C++ and SQL.


• Perform analytical support and provide insights regarding a wide array of business initiatives.


• Work individually or as part of a team on data science projects and work closely with business partners.


• Perform Data wrangling activities and develop statistical/machine learning models using various techniques (supervised, unsupervised, semi-supervised) and technologies including but not limited to Python, R, SAS, Spark, H2O, Aster etc.


• Provide solutions to business needs and analyze work flow processes to make recommendations for process improvement in risk management


• Collaborate and consult with peers, colleagues, managers and regulators to resolve issues and achieve goals.

Required Qualifications :

• 1-3 years of relevant experience in Quantitative Analytics, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.


• BS/BA degree or higher in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis.


• Experience in various aspects of Machine Learning such as data analysis, feature engineering, feature extraction, model training and validation is a must.



• Experience in at least one of supervised, unsupervised, semi-supervise learning and time series analysis.


• Strong practical experience with Python.


• Exposure to SQL, Deep-learning, and Artificial intelligence techniques.


• Good command over MS Office tools - PowerPoint, Excel and data management.

Desired Qualifications:

• Strong understanding of data wrangling and preparation techniques both in single and multithreaded systems in Pandas, Numpy, RDD and spark data-frames.


• Excellent command over supervised, unsupervised and semi-supervised techniques including but not limited to Random Forest, GBM, Ridge-Lasso-ElasticNet, XGboost etc. Time-series techniques like Arima (and the family), Arch, Garch etc.


• Working expertise in Tensorflow, Keras or Pytorch would be added advantage.


• Working expertise on PySpark, H2O would be an added advantage


• Working expertise on Finance or customer analytics would be an added advantage.


• Excellent understanding of model metrics including AUC, ROC, CAP-curve, F-statistics etc. with clear understanding of how model performance is tuned


• Strong programing skills.


• Expertise in multiple analytic tools : R, Python, SAS.


• Big Data skills - Aster, Hadoop, SPARK, H20 and various big data distributions like Hortonworks and MapR.


• Experience on non-structured data analysis - NLP, Text mining, Image/Voice processing, digital analytics.

Job Expectations:

• Person would be required to work individually or as part of a team on data science projects and work closely with business partners across the organization.


• He/she would be developing statistical/machine learning models using various techniques (supervised, unsupervised, semi-supervised) and technologies including but not limited to SAS, R, Python, Spark, H2O, Aster etc.


• Work closely with data engineers, BI and UI specialists and deliver top notch analytical solution for the bank.


• Define business problem and translate it into analytical problem.


• Adapt at attracting, hiring and retaining top notch data science talents and build world class team.


• Help create conducive environment for nurturing and growing talents.

Department Overview

EADS is the central analytics group tasked with solving high-impact business challenges and standing up cutting-edge analytical capabilities to be shared across Wells Fargo's analytic community. We are looking for a high performer to join our team and help us solve challenging and interesting business problems through rigorous data analysis and predictive modeling. In this highly consultative and visible role, you will support development analytic projects from multiple business lines using various technology and techniques ranging from but not limited to supervised, unsupervised and semi-supervised machine learning, deep-learning, NLP, optimization algorithms.

About the Role

This is a partner-facing role and is responsible for delivering high impact analytic and data science projects across enterprise functions (DMI & COO)

We Value Diversity

At Wells Fargo, we believe in diversity, equity and inclusion in the workplace accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.

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.

Candidates applying to job openings posted in US:All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.