Job Purpose
The Data Science team builds solutions that help bankers, customers, and markets better understand risk and opportunity for a diverse set of functions. We use natural language processing, deep learning, classification, regression, and outlier detection to expose previously hidden relationships and provide pertinent details to decision makers just as they are needed. Our model pipelines are built using combinations of Databricks, Python/Conda/Jupyter, R, and Stan, and the results are delivered via visualizations built in D3, Tableau, Spreadsheets, or directly in applications.
Accountabilities
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product & services that customer loves
- Leverage a broad stack of technologies — Python, R, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Skills
- Customer first: You love the process of analysing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
- Innovative: You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
- Creative: You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
- A leader: You challenge conventional thinking and work with stakeholders to identify and improve the status quo. Your passionate about talent development for your own team and beyond.
- Technical: You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
- Statistically minded: You’ve built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
- A data guru: “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyse data from a variety of sources and structures. You know understanding the data is often the key to great data science.
Basic Qualifications
- Bachelor’s Degree plus 5 years of experience in data analytics, or master’s degree plus 3 years in data analytics, or PhD
- At least 2 year of experience in open source programming languages for large scale data analysis
- At least 3 years of experience with machine learning
- At least 2 years of experience with relational databases
Preferred Qualifications
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics, or PhD in “STEM” field
- At least 3 years’ experience in Python, Scala, or R
- At least 3 years’ experience with SQL
- At least 1 year of experience working with Cloud services like Oracle, AWS