CPS Energy is the nation's largest municipally owned energy company, delivering affordable and reliable power to San Antonio and its surrounding areas. By leveraging a diversified portfolio of fuels, the company remains committed to clean energy, innovation, and energy efficiency.

For those interested in joining CPS Energy as a Machine Learning Engineer, the successful candidate will possess a strong foundation in Python, SQL, and advanced data modeling. Applicants should excel in transforming and analyzing large datasets while effectively communicating complex technical concepts to non-technical stakeholders. The role involves partnering with business leaders to drive informed decisions and ensuring the development of high-quality, reproducible products that align with customer preferences and business objectives.

This guide will provide you with insights and tips to navigate the interview process for this exciting position.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining CPS Energy as a Machine Learning Engineer. Whether you were contacted by a CPS Energy recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to 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. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the CPS Energy Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the CPS Energy Machine Learning Engineer hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the CPS Energy Machine Learning Engineer role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around CPS Energy’s data systems, ETL pipelines, and SQL queries.

In the case of machine learning roles, take-home assignments regarding predictive modeling, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

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

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the CPS Energy office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Machine Learning Engineer role at CPS Energy.

Quick Tips For CPS Energy Machine Learning Engineer Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your CPS Energy interview include:

• Demonstrate Initiative: CPS Energy values individuals who are not satisfied with the status quo. Showcase your innovative thinking and how you could twist data to gain new insights.
• Effective Communication: Be prepared to translate complex analytical and technical concepts to non-technical employees. Demonstrating this skill during your interview will show your capability to enable understanding and drive informed business decisions.
• Know the Tools: Brush up on your knowledge of data science analytical tools like Hadoop, Spark, Alteryx, Oracle SQL, Jupyter Notebooks, and Python. Your ability to iterate fast can help demonstrate your efficiency in reducing time-to-market for products.

Typically, interviews at Cps Energy vary by role and team, but commonly Machine Learning Engineer interviews follow a fairly standardized process across these question topics.

• Select the top 3 departments with at least ten employees and rank them by the percentage of employees making over 100K. Given employees and departments tables, select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary. Return the percentage of employees making over 100K, department name, and the number of employees.

What is the average salary for a Machine Learning Engineer at Cps Energy?

Q: What are the primary responsibilities of a Machine Learning Engineer at CPS Energy?

A: As a Machine Learning Engineer at CPS Energy, you'll translate complex analytical concepts to non-technical employees, partner with business leaders to define and solve problems, and build large information sets from structured and unstructured data. You'll also develop and maintain a robust library of reusable algorithms and work to drive informed business decisions.

Q: What qualifications are required for the Machine Learning Engineer position?

A: Candidates need a Master’s degree in Computer Science, Engineering, Applied Mathematics, Quantitative Economics, Statistics, or a related field. Proficiency in Python and SQL, experience with statistical techniques, advanced data visualization, predictive modeling, and machine learning libraries like Scikit-learn, TensorFlow, and PyTorch are also required.

Q: What skills and competencies are critical for success in this role?

A: Key skills include proficiency in Python and SQL, advanced data modeling, data visualization, and using machine learning libraries. Competencies such as effective communication, initiative, continuous improvement, and the ability to work with ambiguity are essential.

Q: How does CPS Energy support professional development for their employees?

A: CPS Energy offers opportunities for continuous learning and development, including support for certifications like the Associate Certified Analytics Professional (aCAP). They also encourage collaboration across departments and provide a stimulating environment to tackle complex problems.

Q: What is the company culture like at CPS Energy?

A: CPS Energy prides itself on a collaborative and innovative culture. They value initiative, continuous improvement, and effective communication. The company is committed to making a difference in customer experience and is focused on enhancing the community's growth and success.

Looking to be part of a dynamic team at the forefront of the energy sector? A Machine Learning Engineer position at CPS Energy could be your next exciting career move! As a part of our Advanced Analytics & Intelligence team, you'll be challenged to twist data for new insights and partner with business leaders to solve complex problems and drive innovation. Mastery in Python, SQL, statistical techniques, and advanced data visualization are vital as you iteratively create high-quality, reproducible products that can transform data into actionable business strategies. CPS Energy is not just about energy; it's about powering the growth and success of our community with a commitment to clean energy and innovation.

If you want more insights about the company, check out our main CPS Energy Interview Guide, where we have covered many interview questions that could be asked. 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 CPS Energy machine learning engineer interview questions and challenges.

You can check out all our company interview guides for better preparation. Good luck with your interview!