It’s important to evaluate a statistician’s technical skills during the interview process to gauge whether they have the expertise required for the role. Here are some suggestions:

Ask questions about the statistical methods and techniques they are familiar with. A good statistician should have extensive experience with common methods like regression analysis, hypothesis testing, statistical modeling, experimental design, as well as newer machine learning and AI techniques. Probe the depth of their knowledge in these areas with specific questions. You want someone who can expertly apply different statistical approaches to solve a wide variety of business and research problems.

Inquire about the statistical software packages they are proficient in. Most statisticians should be highly skilled in big-name platforms like R, Python, SAS, SPSS, and Stata. But also consider any specialized packages used in your industry. Understand not just their experience level, but advanced skills like expertise in programming languages used for statistical computing. You need someone who can leverage powerful tools to quickly and efficiently handle complex analyses.

Present a brief sample business problem and have them walk through how they would approach analyzing it statistically from start to finish. Pay attention to how methodically and clearly they think through scoping the problem, gathering relevant data, choosing appropriate techniques, outlining assumptions, performing procedures, interpreting results, documenting findings, and addressing limitations. Their process should be meticulous yet easy to follow.

Ask for an example of a past project they led that involved substantial statistical work. Listen for how they overcame obstacles, validated assumptions, evaluated alternate methodologies, and ensured rigorous quality standards. Critically assess if their approach seems repeatable, produces defensible conclusions, and delivers tangible impact. You want a statistician able to manage in-depth endeavors of strategic importance.

Inquire about their academic and professional training. A relevant Master’s degree or PhD is standard for many roles. Similarly, certifications demonstrate ongoing education. But experience matters greatly too; someone with 10+ years of practical application may be your best fit versus a new grad. Regardless, they should stay up-to-date in their field through conferences, publications, and lifelong learning.

Evaluate their communication skills. Strong statisticians Translate complex analyses into clear, visual, and actionable insights for non-technical colleagues and management. They should be comfortable collaborating across departments, public speaking, creating reports/presentations, and clearly explaining the significance and limitations of results. Exceptional interpersonal abilities are a must for this role.

Consider giving them sample data and asking them to quickly analyze, summarize, and present findings. How polished, organized and insightful are they on their feet? Do they generate quality graphs, highlight strong and weak predictors, and propose next steps in a concise yet compelling manner? Improv scenarios like this demonstrate “on-the-job” caliber.

Ask about challenges they faced and lessons learned. Admits of past failures or limitations show humility and growth potential. Similarly, describe a time they disagreed with a client or team and how they navigated differing perspectives. You need someone assertive yet flexible and collaborative enough to operate effectively in ambiguous environments.

Evaluate their passion for and commitment to statistics as a career. Stars in this field continuously expand their skillset, adopt new techniques as they emerge and value both the technical and “soft” sides of analysis. Enthusiasm, positive attitude and drive to deliver impact through data should be major selling points.

Thoroughly considering all of these technical and soft skills areas will give you a well-rounded view of statistician candidates and help identify the best fit for your specific needs based on qualifications, experience and intangible factors. With the right evaluation approach, you can confidently select someone optimally equipped to succeed in the role.