Software Engineering Advisor-Hybrid

As a Software Engineering Advisor at Cigna-Evernorth Services Inc., your responsibilities include developing and modifying complex software programs that support various Machine Learning and AI initiatives. You'll collaborate closely with product development teams to ensure best practices are followed, and you'll conduct thorough quality assurance reviews. Additionally, you'll identify process enhancements, serve as a subject matter expert, and provide technical guidance on complex technology components.

To qualify for the Software Engineering Advisor position at Cigna-Evernorth Services Inc., candidates should hold a Master’s degree or its foreign equivalent in Computer Science, Computer Engineering, Data Science, or a related field. A minimum of 2 years of experience in a related occupation is required, along with experience in machine learning models, SQL queries, and technologies like R, Python, and Tableau.

Yes, the Software Engineering Advisor role at Cigna-Evernorth Services Inc. offers the flexibility of hybrid work. You can work from home occasionally, facilitating a better work-life balance. However, it is essential to have a reliable internet connection with specific speed requirements to ensure seamless communication and work efficiency.

For the Software Engineering Advisor position at Cigna-Evernorth Services Inc., candidates should expect up to 25% domestic travel. This allows for collaborative opportunities with teams and clients while still maintaining a significant portion of remote work flexibility.

A Software Engineering Advisor at Cigna-Evernorth Services Inc. should have experience with several technologies, including SQL for custom queries, R and Python for algorithm development, and data visualization tools such as Tableau. Familiarity with Java, Shell Scripting, and machine learning approaches will also be beneficial in this role.

When discussing your experience with Machine Learning projects, focus on specific projects where you played a pivotal role. Describe your responsibilities, the technologies you used, and the outcome of the projects. Highlight any relevant challenges you overcame and how your contributions were crucial to the project's success.

To ensure quality assurance in software development, I regularly conduct detailed code reviews and implement testing protocols to identify issues early. I also advocate for developing clear specifications and encourage collaboration among team members to follow best practices and standards. Sharing responsibility for the quality of each deliverable is also crucial.

When troubleshooting a complex software issue, I first replicate the problem to understand the context. Then, I conduct a root cause analysis to identify any underlying issues, utilizing logs and error messages. Once diagnosed, I can implement corrective actions and document the process to share knowledge with the team for future prevention.

In my previous roles, I have leveraged data visualization tools, particularly Tableau, to represent complex healthcare data in an easily interpretable format. I focus on storytelling through my visualizations, ensuring that insights are clear and actionable for stakeholders. Providing context around the data helps in making informed decisions.

To prioritize my workload, I evaluate deadlines and project importance, often using a priority matrix. I communicate regularly with stakeholders to manage their expectations and proactively address any shifting priorities. Staying organized with task management tools allows me to keep everything on track and visible.

In a hybrid work environment, I utilize various collaboration tools like Slack and Microsoft Teams for consistent communication. Regular virtual meetings help maintain transparency, while setting clear goals ensures that teams work cohesively. Fostering an inclusive culture that encourages input from all team members, regardless of location, is also important.

In my past roles, I developed technical standards by first gathering input from various stakeholders to ensure the guidelines met everyone's needs. I would then document these standards comprehensively and facilitate training sessions for teams to ensure everyone understood and could implement them effectively.

To stay current with advancements in Machine Learning, I regularly attend workshops, webinars, and industry conferences. I also participate in online forums and read recent industry publications to learn about new technologies and methodologies. Networking with peers offers insight into what works well in their applications.

Documentation is crucial in software engineering as it provides a clear reference point for current and future developers. It ensures knowledge transfer within teams and across projects. Well-documented code and processes lead to more efficient troubleshooting and onboarding, ultimately enhancing productivity.

My approach to implementing feedback involves active listening and understanding the perspective of those providing it. I take the time to analyze the feedback, share it with the relevant team members, and discuss how we can improve our processes or deliverables based on those insights. Continuous improvement is vital in software engineering.