Data Science, Manager

As a Data Science Manager at Pfizer, your primary responsibility will be to provide data science insights that help drive decision-making for various brands. You will develop and execute machine learning models, interpret them, and collaborate closely with the commercial team to frame key business questions and develop actionable strategies. You will also support sales teams in executing brand strategies, using your analytical expertise to translate complex data into meaningful insights that guide business operations.

To be considered for the Data Science Manager role at Pfizer, candidates should possess a Bachelor’s degree in a quantitative discipline, such as engineering or data science, along with four or more years of relevant experience. Alternatively, a Master’s degree combined with two years of experience, or a PhD in a related field, may also qualify you for this position. Proficiency in Python, R, and a strong understanding of machine learning technologies will be essential for success in this role.

Data Science Managers at Pfizer can expect a dynamic, fast-paced, and highly collaborative work environment. The Global Commercial Analytics team works closely together, leveraging diverse skill sets to tackle a broad range of strategic business topics. Due to the nature of the role, you will often be engaging with sales, marketing, and various analytics teams, making it essential to thrive in a collaborative setting where you can influence stakeholders and drive impactful insights.

Pfizer is committed to the professional growth of its employees, including Data Science Managers. Through opportunities for ongoing training, mentorship programs, and access to a wealth of resources, Pfizer fosters an environment where employees can develop their skills continuously. The company encourages collaboration and innovative thinking, allowing you to expand your knowledge base and advance your career within a supportive framework.

As a Data Science Manager at Pfizer, you’ll enjoy a competitive salary, eligibility for performance-based bonuses, and a comprehensive benefits package that includes a 401(k) plan, paid time off, health benefits (including medical, dental, and vision), and various wellness programs. The company values work-life balance and provides flexibility in work location, with a hybrid model that allows for 2-3 days onsite each week.

When answering this question, you should detail specific machine learning projects you've worked on, emphasizing your role in framing the problem, selecting the right model, and analyzing results. Discuss how your insights influenced business decisions and the impact on brand strategy, demonstrating your ability to translate complex data into actionable recommendations.

In responding, outline your method for assessing project impact, timelines, and resources. Explain your collaborative approach in gathering inputs from stakeholders and how you ensure that high-priority projects are addressed while maintaining flexibility for evolving needs within the team and organization.

Emphasize your ability to simplify complex data and use visuals or storytelling techniques to engage the audience. Share an example where you successfully conveyed technical information to stakeholders, demonstrating your skills in making complex insights accessible and relevant to their strategies.

Your answer should highlight specific resources such as journals, online courses, webinars, or networking groups. Mention how you apply this knowledge in your work, staying ahead of the curve and ensuring that your approaches and models utilize the latest techniques and data sources available.

Share a specific instance where your analytical insights supported a key decision in sales or marketing. Describe how the collaboration occurred, what data or models you provided, and the outcome that resulted from this teamwork, demonstrating your value as a Data Science Manager.

List the tools (like Python, R, and SQL) and describe how you’ve leveraged them in your analytics work. Provide examples of how these tools have enabled you to produce insightful reports, automate processes, or improve data accuracy, showcasing your technical expertise relevant to the Data Science Manager role.

Discuss the importance of building relationships across teams, understanding business needs, and communicating results effectively. Highlight your approach to influencing key decision-makers and how you ensure that insights translate into actionable strategies that drive tangible change.

Outline your approach to presenting data respectfully while backing it up with solid evidence. Emphasize the importance of listening to feedback, being open to discussions, and finding common ground that encourages data-driven decisions while fostering a collaborative environment.

Discuss how creativity helps you in finding unique solutions to data challenges and in presenting insights in ways that resonate with stakeholders. Provide examples of innovative ways you’ve visualized data or approached problem-solving that enhanced the value of your analyses.

Your answer should express your enthusiasm for Pfizer's mission and values, connecting them with your passions and career goals. Reflect on what excites you about the opportunity to influence patient outcomes and how you see yourself contributing to the company’s innovative data-driven initiatives.