and Huntington interview process & guide 2026
Everything we know about interviewing at and Huntington: the process stage by stage, what each round tests, and compensation by level.
- 1Phone Screen
- 2HR Phone Screen
- 3Hiring Manager Interview
- 4Core Interview Stages
- 5Technical Assessment and Panel/In-Person Rounds
Interviewing at and Huntington
You will go through a multi-touch screening and interview loop that mixes recruiter or HR screens, one-on-one hiring manager conversations, and a panel format. Across roles, the process explicitly tests both behavioral fit and technical depth, with multiple steps combining technical and behavioral evaluation.
The interview content is heavily weighted toward technical competency in analytics and engineering contexts: Statistical Analysis is the top topic (percentile 100), and Solutions Architecture (percentile 100), Quality Assurance Engineering (percentile 100), Operations Management (percentile 100), and Business Analysis (percentile 100) also appear at the highest level. You should also expect common modeling and assumptions topics like Logistic Regression (percentile 96) and Linear Regression Assumptions (percentile 92), plus architecture themes that include Data Architecture (percentile 96) and Cloud Architecture (percentile 93).
Timeline details and post-interview steps are not specified in the provided data, but the loop steps reported cover Phone Screen and HR Phone Screen, then Core Interview Stages and In-Person or Technical Assessment style rounds, often including panels and hiring manager conversations. Based on the aggregated candidate reports, offer rate is reported as 0.0%, and positive sentiment is 60.6%, so you should treat this as a high-selection loop where doing the basics well is necessary but not clearly sufficient.
The strongest signal from the topic data is that they test statistical thinking and system thinking together, with Statistical Analysis and Solutions Architecture at percentile 100, plus QA Engineering and multiple “architecture” topics. Prepare to connect your analytics work to design choices, testing, and data reliability.
How hard is the and Huntington interview?
Aggregated from 433 interview experiencesAbout 1 in 2 candidates with a known outcome convert.
The interview process, end to end
5 rounds · based on 433 candidate reports- 1Phone Screen
You start with a recruiter or HR phone screen. The reported focus is baseline experience and fit, including behavioral alignment, and may include salary expectations and logistics.
- 2HR Phone Screen
Some roles report an additional HR call that validates baseline qualifications, salary expectations, and resume keyword alignment. It is positioned as a verification and fit check.
- 3Hiring Manager Interview
You then meet the hiring manager in a 1:1 conversation focusing on resume fit and role alignment. One-on-one interview descriptions include in-depth discussion about your understanding of commercial banking data, and cultural fit.
- 4Core Interview Stages
Core stages combine technical and behavioral rounds and may run as panel sessions or back-to-back interviews with engineering managers. You may also meet the hiring manager with a panel of peers or cross-functional partners using traditional interview questions.
- 5Technical Assessment and Panel/In-Person Rounds
Depending on the role, you may do a technical assessment including live coding, data manipulation, SQL queries, or building a dashboard from a sample dataset. Some roles also report in-person interviews with hiring managers and department heads plus cross-functional stakeholder interviews.
What and Huntington actually tests for
How prominent each skill is across reported loopsFind the guide for your role
This is your next step: open the guide for the role you are interviewing for. Each one carries the questions and Huntington interviewers actually ask that position, the loop structure, and pay by level.
What and Huntington pays, by level
Estimated total compensation: base salary plus stock and annual cash bonus.
What separates offers from rejections
Patterns from candidates who got offers, and the mistakes that most often sink a loop.
Do this
- Be ready to explain your reasoning for statistical questions, including Logistic Regression and Linear Regression Assumptions. Don’t just compute, tie your answers back to assumptions and what those imply.
- Prepare to discuss architecture and data architecture decisions, including how you would structure systems and data for reliability. Use examples where you can describe tradeoffs and constraints, since Solutions Architecture and Data Architecture are both top-percentile topics.
- Treat QA and testing as a core competency, not a side topic. Be specific about how you validate results, handle edge cases, and ensure quality in your workflows.
- For behavioral and stakeholder communication, align your stories to cross-functional teamwork and clarity. Panel and hiring manager interviews include behavioral evaluation and cultural fit, and Stakeholder Communication is highly prominent (percentile 96).
Avoid this
- Don’t assume the loop is only behavioral or only technical. The reported process repeatedly combines technical and behavioral evaluation in panel and core stages.
- Don’t underprepare on regression assumptions and data quality topics. Data Quality Management appears (percentile 52), and Linear Regression Assumptions is very prominent (percentile 92), so shallow coverage is risky.
- Don’t ignore architecture and cloud design conversations. Cloud Architecture (percentile 93) and Solutions Architecture (percentile 100) are top-level topics, and they show up across roles.
- Don’t rely on offer outcomes from this dataset as guidance, since offer rate is reported as 0.0%. Focus on maximizing performance against the listed technical and behavioral competencies rather than expecting loose thresholds.
and Huntington interview FAQ
Answered from real candidate and workplace dataHow long is the interview process, and what is the timeline?
The provided data lists the steps in the loop but does not provide an overall timeline duration. It specifies several components, including Phone Screen, HR Phone Screen, Hiring Manager Interview, and technical or in-person style rounds, but not how many days the full process takes.
What are the hardest topics I should prepare for?
Difficulty levels from candidate reports are mostly medium (57.9%), with easy at 33.0%, hard at 7.1%, and very hard at 2.1%. Topic prominence is also a strong guide, with Statistical Analysis (percentile 100) and Solutions Architecture (percentile 100) at the highest level, plus QA Engineering (percentile 100) and Operations Management (percentile 100).
What does the technical assessment look like?
For the Technical Assessment step (reported by 2 roles), the data mentions deep dives into technical skills, live coding challenges, and discussions of past projects and architectural decisions. It also mentions practical evaluation that can include data manipulation, SQL queries, or building a dashboard using a sample dataset.
Is there a lot of regression, ML, or math in the loop?
Yes. Logistic Regression is prominent (percentile 96) and Linear Regression Assumptions is also prominent (percentile 92). The panel interview descriptions also mention potential Machine Learning basics.
Do they care about stakeholder communication and behavior?
Yes. Stakeholder Communication is highly prominent (percentile 96), and multiple reported steps include behavioral evaluation: panel interviews assess behavioral and teamwork skills, and hiring manager interviews include cultural fit and resume fit discussions.
Should I expect an offer from my interviews here?
The aggregated candidate reports show an offer rate of 0.0%. The dataset also shows positive sentiment of 60.6%, but it does not provide a breakdown of why candidates did or did not receive offers.
What people say about and Huntington
Verbatim snippets from employee and candidate reviews“The work-life balance and company culture are excellent.”
“While the work-life balance is commendable, improvements in pay and technology are needed.”
“Compensation is mediocre, and developers face challenges with slow laptops.”
“The work environment is positive, supported by a great team of people.”
“Management should consider increasing pay to improve employee retention.”
“Overall, it's a decent place to work.”
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