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Sr. Data Scientist

Northern Trust · Chicago, IL · $114,500–$194,700 a year · Full time

Posted Sep 15, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Walk me through a time you pulled data from several sources, like a database, flat files and an API, into one training set. What went wrong along the way?

What they are checking: Whether they have done the unglamorous data acquisition work themselves rather than receiving clean tables from someone else.

Describe a model you built that a business partner did not trust at first. How did you win them over, or did you?

What they are checking: Whether they can explain results plainly and accept that adoption, not accuracy alone, decides whether the work matters.

Tell me about a time the right answer was a simple model or no model at all.

What they are checking: Whether they put the business result ahead of showing off technique, which is a sign of senior judgment.

What would you do

You get a raw dataset with fields nobody has documented. How do you work out what each field really means before you model anything?

What they are checking: Whether they lean on descriptive statistics and domain experts instead of guessing, since wrong field meanings poison every model downstream.

Your model performs well in testing, but a month after launch the predictions start drifting. What do you check first?

What they are checking: Whether they have a calm, ordered way to separate data changes, pipeline bugs and real shifts in behavior.

In a regulated firm like ours, models often get reviewed by a validation team. How do you write and document your work so it survives that review?

What they are checking: Whether they expect scrutiny and build reproducibility and clear assumptions in from the start.

About the work

What unit tests and data quality checks do you put on a pipeline so a model never trains on bad data without anyone noticing?

What they are checking: Whether they treat trusted data as an engineering problem with automated checks, not a one-time manual look.

How do you split data into training, validation and test sets for a time series problem, and what mistake do people make there?

What they are checking: Whether they understand leakage from the future, which quietly inflates results on financial time series.

Tell me about an ensemble method you proposed. Why did it beat a single model, and how did you prove that?

What they are checking: Whether they can justify added model complexity with honest out-of-sample evidence rather than a leaderboard number.

When would you reach for an unsupervised approach instead of a supervised one on a business problem at a bank?

What they are checking: Whether they choose methods from the shape of the problem and available labels, not from habit.

How do you structure Python code for a data science project so someone else can rerun it six months from now?

What they are checking: Whether they write production-minded software, which the posting stresses, rather than notebooks only they can run.

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The full job description

As published by Northern Trust.

About Northern Trust As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world’s most successful individuals, families, corporations and institutions. Since 1889, we have aligned our efforts with our three guiding Principles That Endure: Service, Expertise, and Integrity. Together, they reflect the three cornerstones of business conduct which we strive to instill in our employees, whom we call partners, and to provide to our clients and the communities we serve worldwide. With more than 135 years of financial experience and over 24,000 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 • May 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 some 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 • Solves complex problems • Takes a new perspective on existing solutions • Exercises judgment based on the analysis of multiple sources of information • Impacts a range of customer, operational, project or service activities within own team and other related teams • Works within broad guidelines and 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 in-depth conceptual and practical knowledge in own job discipline and basic knowledge of related job disciplines • Applies best practices and how own area integrates with others • Explains difficult or sensitive information; works to build consensus Experience :• Computer Science degree (undergraduate or graduate level) and strong statistical background. Data Science specific graduate work, Finance sector experience or coursework preferred • Acts as a resource for colleagues with less experience; • May lead small projects with manageable risks and resource requirements Salary Range: $114,500 - 194,700 USD Salary range is a good faith estimate of base pay. Northern Trust provides a comprehensive benefits package including retirement benefits (401k and pension), health and welfare benefits (medical, dental, vision, spending accounts and disability), paid time off, parental and caregiver leave, life & accident insurance, and other voluntary and well-being benefits. Northern Trust also provides a discretionary bonus program that may include an equity component. Work Authorization Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. Northern Trust will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa). Working with Us As a Northern Trust partner, you will be part of a flexible and collaborative work culture, which has a strong history of financial strength and stability. Movement within the organization is encouraged, senior leaders are accessible, and you can take pride in working for a company committed to an inclusive workplace and assisting the communities we serve. Philanthropy is deeply rooted in Northern Trust’s history and is an essential element of our culture. Employees around the world give their time and talent to work for the greater good of their communities. Reasonable Accommodation Northern Trust is committed to working with and providing adjustments to individuals with health conditions and disabilities. If you need a reasonable accommodation for any part of the employment process, please email our HR Service Center at MyHRHelp@ntrs.com , or alternatively you can discuss your individual requirements with the recruiter you are working with.

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