Sponsorship is NOT available for this position

This role offers a hybrid work schedule; offering the flexibility to work remotely two days a week, while providing the opportunity for in-person collaboration.

As a Data Scientist on the Data Academy team, you'll be at the intersection of data science and education. You'll apply your data science skillset to analyze key performance data, and use those insights to develop and enhance the Data Academy's curriculum.

POSITION RESPONSIBILITIES:

• Aid in the development and implementation of data science and data analysis curriculum under the guidance of more experienced data scientist.

• Work with large and complex data sets to solve unstructured problems using different analytical and statistical approaches for multiple products.

• Conduct sourcing, ingesting, and cleaning of data sets in preparation for analysis.  Ensure data is stable, accounting for data drift in development and production.

• Establish and document best practices for econometric, statistical and machine learning models for various problems inclusive of classification, clustering, pattern analysis, sampling, and simulations.

• Review own code to ensure it is efficient, accurate, and using best practices.

• Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite.  Identify risk-related issues needing escalation to management.

• Promote an environment that supports diversity and reflects the M&T Bank brand.

• Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.

• Complete other related duties as assigned.

MINIMUM QUALIFICATIONS REQUIRED:

• Bachelor’s degree and a minimum of 3 years related experience, or in lieu of a degree, a combined minimum of 7 years higher education and/ or work experience, including a minimum of 3 years related experience

• Experience working with statistics or data science principles, such as AB testing, sample selection, hypothesis testing, modeling bias.

• Proficiency with pertinent statistical software and languages and tools

• Intermediate level knowledge with one or more of the following: SQL, Tableau, Power BI, Python, R and Alteryx

• Experience with various hybrid databases both on premise and in the cloud

• Understanding of modeling techniques such as Bayesian modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statistics

• Experience analyzing large data sets

IDEAL QUALIFICATIONS PREFERRED:

• Masters’ of Science or Doctorate degree in Statistics, Economics, Finance or related field in the quantitative social, physical or engineering sciences, with proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management

• Experience leveraging econometric/statistical techniques, including time-series analysis, panel data methods and logistic regression

• Tactical experience with pertinent statistical software and languages and tools

Location