Stord is a rapidly growing supply chain software company that provides innovative logistics solutions to help businesses optimize their operations. Specializing in cloud-based technology, Stord integrates various supply chain facets, from warehousing to transportation, making them a major player in logistics software.

Stepping into a Data Scientist role at Stord means joining a dynamic team that leverages data to solve complex logistics challenges. This position demands strong analytical skills, proficiency in machine learning algorithms, predictive modeling, and a deep understanding of logistics and supply chain management.

If you're preparing to interview for this position, this guide on Interview Query is for you. It will walk you through the interview process, commonly asked questions, and provide valuable tips to help you excel. Let’s dive in!

Submitting Your Application

The first step in joining Stord as a Data Scientist is to submit a compelling application that reflects your technical skills and interest in the role. Whether you've been contacted by a Stord recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV to meet the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Highlight relevant skills and mention work experiences that directly align with the Data Scientist role.

Recruiter/Hiring Manager Call Screening

If your CV makes the cut, a recruiter from Stord's Talent Acquisition Team will reach out to verify key details about your experiences and skill level. Behavioral questions may also be a part of this screening process.

Sometimes, the Stord data scientist hiring manager will be present during this call to answer any queries you may have about the role and the company itself. They might also engage in surface-level technical and behavioral discussions.

The recruiter call usually lasts about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will earn you an invitation for the technical screening round. Technical screenings for the Stord Data Scientist role are usually conducted virtually, including video conferencing and screen sharing. Questions in this 1-hour long stage may revolve around Stord’s data systems, ETL pipelines, and SQL queries.

For data scientist roles, take-home assignments concerning product metrics, analytics, and data visualization are often included. Your proficiency in hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed.

Depending on the seniority of the position, case studies and similar real-scenario problems may be assigned.

Onsite Interview Rounds

Following a second recruiter call outlining the next stage, you'll be invited to attend the onsite interview loop. At the Stord office, multiple interview rounds will be conducted throughout the day, focusing on your technical prowess, including programming and ML modeling capabilities.

If you were given take-home exercises, a presentation round might be part of the onsite interview for the Data Scientist role at Stord.

Quick Tips For Stord Data Scientist Interviews

Here are three tips to help you excel in your Stord Data Scientist interview, based on interview experiences:

• Understand Stord’s Business Model: Get familiar with Stord's logistics and supply chain solutions. Understanding the core business will help you tailor your responses.
• Be Proficient in SQL: Many interviewees report that SQL questions are prevalent. Make sure you practice SQL queries extensively using platforms like Interview Query.
• Prepare for Behavioral Questions: Stord values cultural fit, so be ready to discuss your previous teamwork experiences, how you handle challenges, and how you align with Stord's values.

Typically, interviews at Stord vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• How would you modify your neural network to better distinguish between pugs and pit bulls? You built a robot that searches for lost dogs using a convolutional neural network to classify dog breeds. The network struggles to differentiate pugs and pit bulls due to mislabeled training data and poor viewing conditions. How would you adjust the neural network to improve its accuracy in these scenarios?

If you want more insights about the company, check out our main Stord Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Stord’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Stord Data Scientist interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!