Bristol-Myers Squibb (BMS) is a global biopharmaceutical company committed to discovering, developing, and delivering innovative medicines that help patients prevail over serious diseases. BMS leverages cutting-edge science, technology, and a dedication to patient care to address some of the most challenging health issues of our time.

The Data Scientist position at BMS is integral in supporting operational analytics across Global Product & Supply (GPS). This role involves developing, deploying, and maintaining advanced analytics capabilities, including predictive modeling, simulation, and optimization. Responsibilities include building scalable data pipelines, implementing MLOps practices, and collaborating with cross-functional teams to derive actionable insights. With a focus on machine learning and data engineering, candidates must proficiently handle large datasets, advanced SQL, and AI technologies to drive business innovation and patient outcomes.

For those interested, Interview Query provides comprehensive guides to navigate the interview process, detail common questions, and offer invaluable tips for success.

The Interview Process at Bristol-Myers Squibb for a Data Scientist Position

Landing a Data Scientist position at Bristol-Myers Squibb (BMS) involves a multi-step interview process designed to assess both technical expertise and cultural fit. Here’s a detailed guide to what you can expect:

Submitting Your Application

The journey begins with submitting a strong application through the BMS career portal. Tailor your CV and cover letter to align with the job description, emphasizing relevant skills and experiences. Utilize industry-specific keywords to ensure your application stands out and passes through automated screening processes.

Recruiter/Hiring Manager Call Screening

If your application is shortlisted, a recruiter from BMS’s Talent Acquisition Team will reach out for an initial phone screen. This is primarily a discussion about your experience, skillset, and what you've mentioned in your application. They may also introduce you to the company's role and values. Expect to answer questions like:

• What is your role in your current/previous positions?
• Which tools and technologies have you used extensively?

If your profile fits the role, the recruiter will schedule a virtual interview. This typically includes a technical round followed by an HR interview.

Technical Virtual Interview

The next stage involves a virtual interview that includes both technical and behavioral questions. This round could be conducted via video conferencing, where you'll answer questions about your technical proficiency in areas such as:

• SQL and Python programming
• Data pipelines, analytical engineering, and machine learning models
• Experience with cloud-based environments and data visualization tools

You may also be asked to solve real-time coding problems or present a case study related to data analytics and business problem solving.

Panel Interview and Presentation

If you successfully clear the technical virtual interview, you will be invited to a panel interview. This is a more detailed assessment where you might have to give a presentation on a relevant topic, followed by a Q&A session with a panel of BMS scientists and department heads. This round aims to:

• Evaluate your problem-solving approach
• Gauge how well you can communicate complex information
• Understand your potential fit within the team

Questions could cover areas like:

• How does data analytics drive business decisions at BMS?
• Discuss previous projects where you had to overcome significant challenges

Onsite Interview Rounds

Post the panel interview, you might have another round of interviews conducted onsite or through multiple virtual meetings with different team members. These interviews will dive deeper into your expertise and behavioral competencies. Expect to discuss in detail:

• Your past research activities
• Any domain-specific knowledge (e.g., biopharma, medical analytics)
• Real-world scenarios to test your problem-solving abilities

This stage helps BMS determine if you are a good cultural fit and aligns with the company's goals and values.

Quick Tips For Bristol-Myers Squibb Data Scientist 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 BMS interview include:

• Know the Biopharma Industry: Questions may be standardized and rely heavily on situational scenarios related to biopharma. Understand the industry-specific challenges and how analytics can drive innovation in this field.
• Be Technically Sound: BMS’s data science interviews assess your ability to build and maintain scalable data pipelines and machine learning models. Ensure that you are proficient in SQL, Python, and data visualization tools like Tableau.
• Articulate Clearly: BMS values clear communication. Practice explaining complex technical concepts and data-driven insights in a way that non-technical stakeholders can understand.

Typically, interviews at Bristol Myers Squibb vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• Write a function precision_recall to calculate precision and recall metrics from a 2-D matrix. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: What's the time complexity?

• Write a function perm_palindrome to determine if a permutation of a string can be a palindrome. Given a string str, write a function perm_palindrome to determine whether there exists a permutation of str that is a palindrome.

• Write a function to return any subset of integers that sum to zero without including the number 0. You are given a list of integers called numbers. Write a function to return any subset of numbers where the elements sum to zero and that does not contain the number 0. If there are no combinations, return an empty list.

• Write a function to sum two numeric strings without converting them to integers. Given two strings, num_str1 and num_str2, write a function to sum the two strings together without directly converting them to integers. Return the output in string format.

• What metrics determine ride demand and supply in a ride-sharing marketplace? You work as a data scientist on a ride-sharing marketplace. What metrics would you look at to determine the demand for rides at any point? Additionally, what metrics would tell you if there is high demand and low supply? How can you determine the threshold for when there's too much demand?

• How would you measure the success of Facebook stories without using A/B testing? You are working on Facebook's stories and have found that very few users click through the story functionality. You are tasked with measuring the success of Facebook stories, but you cannot use a standard A/B test. What testing strategies and metrics would you use to determine the success of stories?

• What metrics would you use to rank Twitter users by influence? Let's say that you're given 100 Twitter users. What metrics would you use to rank each user in influence? How would you quantify the influence of a Twitter user?

• What does the distribution of time spent per day on Facebook look like? Describe the distribution of time spent per day on Facebook. What metrics would you use to characterize this distribution?

• Show that if (f_X) is a strictly decreasing function, then (m \geq \mu). Given a continuous random variable (X) with probability density function (f_X(x)), mean (\mu), and median (m), prove that if (f_X) is strictly decreasing, then (m \geq \mu).

• What is the probability of getting a pair in a hand of (N) cards? If you draw (N) cards without replacement from a standard 52-card deck, compute the probability of getting a pair (two cards of the same rank).

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms and explain the tradeoffs between using a bagging algorithm and a boosting algorithm. Provide examples to illustrate the differences.

• How would you design an ML system to extract, transform, and store data from APIs for downstream models? As a machine learning engineer for a large bank, you have access to Reddit and Bloomberg APIs. Design a system that extracts data from these APIs, transforms it, and stores it in a format usable by downstream modeling teams for various applications like risk assessment and marketing.

What is the average salary for a Data Scientist at Bristol-Myers Squibb?

Q: What is the interview process like for a Data Scientist position at Bristol-Myers Squibb?
The interview process usually starts with an HR phone screen to discuss your experience, followed by a virtual interview that includes a technical round and a HR interview. If your profile is well-received, you’ll move on to interviews with a panel. Be prepared for a combination of technical questions and behavioral assessments.

Q: What are some common technical topics I should prepare for?
You should be well-versed in SQL and Python programming, as well as familiar with data engineering tools and machine learning frameworks like TensorFlow, PyTorch, and Scikit-Learn. Experience with cloud-based environments (AWS, Azure) and knowledge of MLOps principles are also advantageous.

Q: What kind of technical skills are required for the Data Scientist role at Bristol-Myers Squibb?
Candidates need to be proficient in Python, R, SQL, and tools like GitHub, Tableau, and dbt. Expertise with cloud-based environments (AWS, Azure), machine learning models, and data pipelines is also expected. Strong analytical thinking, communication skills, and a solid understanding of digital analytics tools are essential.

Q: What should I expect from the panel interview?
The panel interview often includes a presentation, followed by a Q&A session. You may also go through several rounds of interviews focusing on your experience, project management skills, and aptitude for problem-solving. Questions could involve discussions about your past projects, your approach to data analytics, and how you can contribute to the team.

Q: How can I best prepare for an interview at Bristol-Myers Squibb?
Researching the company and the role you're applying for is crucial. Practicing common interview questions, reviewing your technical skills, and being prepared to discuss your past experiences are highly recommended. Resources like Interview Query can be incredibly helpful for preparation.

Navigating the interview process for a Data Scientist position at Bristol-Myers Squibb reveals a multifaceted and comprehensive experience aimed at uncovering technical prowess, problem-solving abilities, and cultural fit. From initial HR screenings to detailed technical rounds and insightful panel interviews that may include presentations, the process ensures a deep dive into candidates' skills and their alignment with the organization's goals. If you want more insights about the company, check out our main Bristol-Myers Squibb Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Bristol-Myers Squibb’s interview process for different positions.

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 Bristol-Myers Squibb Data Scientist interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!