at Northern Trust Company in Chicago, Illinois, United States
Job Description
About Northern Trust:
Northern Trust, a Fortune 500 company, is a globally recognized, award-winning financial institution that has been in continuous operation since 1889.
Northern Trust is proud to provide innovative financial services and guidance to the world's most successful individuals, families, and institutions by remaining true to our enduring principles of service, expertise, and integrity. With more than 130 years of financial experience and over 22,000 partners, we serve the world's most sophisticated clients using leading technology and exceptional service.
Major Duties : Develop software, typically in Python, to independently acquire data from disparate sources (databases, files, APIs, etc.) and combine them into appropriate training , validation and testing datasets
Analyze raw datasets using descriptive statistics, working directly with domain experts to understand the meaning of data fields
Build unit tests, data quality checks and data pipelines to ensure that algorithms use trusted data
Develop and maintain an understanding of many algorithms across supervised learning, unsupervised learning and time series analysis
Propose and develop machine learning ensemble methods that exhibit the best out-of-sample characteristics possible given the input dataset
Utilize expertise in machine learning algorithms to tune algorithms using available hyper-parameters and carefully select feature subsets
Discover biases or leakage in datasets and ensure that train/test splits reflect realistic expectations of real world performance
Run large scale (either in parallel and/or distributed) training and inference jobs on private or public cloud infrastructure
Present findings to internal and external customers using both data science language (F1 scores, regression error, statistical significance, etc.) as well as business domain specific language gained from experience analyzing the data in scope.
Provide guidance to other software development teams as Data Science Lab prototypes are engineered for full production environments
Work across multiple projects in a fluid environment where work is required across the full research lifecycle from forming a hypothesis, acquiring data, and developing ETL-style software to presenting findings.
Plan and execute data science training sessions and hackathons
Work with external parties (vendors, universities, etc.) to incorporate new techniques and tools into the data science lab
Leads others to solve complex problems
Uses sophisticated analytical thought to exercise judgement and identify innovative solutions
Impacts the achievement of customer, operational, project or service objectives
Work is guided by functional policies
Knowledge : Python, Common Python libraries (numpy ,pandas, sklearn, etc.), Linux based operating systems, and basic development tools (Python IDEs, source control, etc.) required
Advanced distributed machine learning frameworks (e.g. Keras, TF, etc.), Azure cloud infrastructure preferred
Requires specialized depth and/or breadth of expertise in own job discipline or field
Interprets internal/external business challenges and recommends best practices to improve products, processes or services
Communicates difficult concepts and negotiates with others to adopt a different point of view
Experience : May lead functional teams or projects with moderate resource requirements, risk, and/or complexity
Computer Science degree (undergraduate or graduate level) and strong statistical background. Data Science specific graduate work, Finance sector experience or coursework preferredEqual Opportunity Employer - minorities/females/veterans/individuals with disabilities/sexual orientation/gender identity
