Decision Sciences Analyst

As a Decision Sciences Analyst at Kobie, you will play a crucial role in analyzing customer data to provide actionable insights for loyalty initiatives. Responsibilities include developing real-time dashboards, collaborating closely with clients to align on objectives, managing audience lists for targeted campaigns, and creating detailed data visualizations for stakeholders. Your expertise will help drive business objectives by extracting key insights from complex data sources, and you'll also work with cross-functional teams to design and enhance new tools to support client goals.

To be successful as a Decision Sciences Analyst at Kobie, candidates should have 2-4+ years of relevant experience in customer analytics or marketing. A Bachelor’s Degree in Statistics, Marketing, Economics, or Computer Science is required, with a Master’s or MBA preferred. Familiarity with data visualization tools such as Tableau or PowerBI, as well as Python and SQL programming skills, are valued. A strong understanding of customer segmentation techniques and solid project management skills will also enhance your candidacy.

Kobie is dedicated to fostering career growth for all teammates, including Decision Sciences Analysts. With a comprehensive people strategy in place, employees are equipped with the tools and guidance needed to advance their career journeys. This includes competitive compensation, 401k matching, annual profit sharing, and bonuses, along with opportunities for professional development and skills enhancement in a supportive environment.

A Decision Sciences Analyst at Kobie should be familiar with various data exploration and visualization tools, especially Tableau, PowerBI, or Sigma. Understanding customer segmentation techniques and being comfortable with data manipulation through Python and SQL are essential skills for effectively analyzing data and delivering insightful recommendations to stakeholders.

Absolutely! At Kobie, diversity and inclusion are celebrated and prioritized. The company is steadfast in creating an environment where all teammates feel welcomed and valued. As a Decision Sciences Analyst, you will be part of a workplace culture that embraces differences, ensuring that everyone’s unique backgrounds and perspectives are respected and incorporated into daily work. Kobie is committed to equity across all levels of the organization.

In your response, emphasize your analytical techniques and tools you use, like RFM and cluster analysis. Discuss how you leverage these methods to derive actionable insights that can inform marketing strategies and enhance customer loyalty, thereby driving value for the client.

Use the STAR method to structure your answer: discuss the Situation, Task, Action, and Result. Highlight your role in managing the project, any challenges faced, the analytical methods you applied, and the results achieved, focusing on how it benefited customer loyalty or drove sales.

Explain that effective data visualization should be clear, concise, and tailored to the audience. Discuss the importance of using engaging formats, focusing on key insights, and ensuring the narrative is coherent while making the data approachable for stakeholders of various expertise levels.

Discuss your approach to prioritization, which involves assessing project impact and urgency while maintaining open communication with clients to manage expectations. Highlight your organizational skills and emphasis on aligning client objectives with project timelines and capabilities.

Share your proficiency with techniques like regression analysis and clustering. Discuss specific scenarios in which these methods helped you uncover critical insights or drive targeted marketing efforts that have significantly contributed to a client’s loyalty program success.

Talk about your thorough understanding of a client's strategy and objectives, which allows you to tailor your insights effectively. Emphasize the importance of building strong relationships with clients to ensure that your recommendations are relevant and facilitate real-world implementation.

Highlight the significant role of collaboration in your work with cross-functional teams such as client services, data engineering, and strategy. Discuss how sharing insights and aligning goals enhances overall project outcomes and ensures that client needs are met effectively.

Discuss your experience with tools like Tableau, PowerBI, or Python for data manipulation and exploration. Emphasize your comfort level with these technologies and how they contribute to the analysis and visualization processes within your projects.

Discuss your preparation process, including organizing your data, creating persuasive visualizations, and anticipating questions or concerns. Emphasize your focus on storytelling with data to engage your audience and convey insights clearly and effectively.

Discuss techniques such as visual storytelling, aligning insights with business objectives, and tailoring your approach to the specific interests of your audience. Highlight the essential role of presenting data in a digestible format to foster engagement and ensure recommendations are well received.