1. What is a Project Manager at Dataiku?

At Dataiku, a Project Manager plays a pivotal role in orchestrating the deployment, adoption, and success of our Everyday AI platform. Unlike generic project management roles, this position sits at the intersection of advanced technology, business strategy, and organizational change. You are not just tracking timelines; you are enabling large organizations to operationalize machine learning and data science at scale.

This role requires navigating complex stakeholder landscapes, often bridging the gap between technical teams (data scientists, engineers, architects) and business leaders. Whether you are focused on Professional Services (guiding customers through implementation), Internal Operations, or specific thematic areas like Corporate Social Responsibility (CSR), your work directly impacts how effectively users can leverage data to drive value. You ensure that ambitious AI initiatives are delivered on time, within scope, and with high adoption rates.

You will likely be working with the Data Science Studio (DSS) platform, helping teams move from raw data to deployed models. The environment is fast-paced and collaborative, requiring you to be a proactive problem solver who can thrive in a hybrid culture that values autonomy and impact.

2. Getting Ready for Your Interviews

Preparing for the Dataiku interview process requires a shift in mindset. You are not just being evaluated on your ability to make a Gantt chart; you are being tested on your ability to manage ambiguity, influence without authority, and understand the nuances of the data lifecycle.

Key evaluation criteria for this role include:

Project Governance & Methodology You must demonstrate a robust command of project management frameworks (Agile, Scrum, Waterfall) and how to adapt them to data projects. Interviewers will evaluate how you structure complex initiatives, manage risks, and handle scope creep in environments where requirements often evolve.

Stakeholder Management & Communication Dataiku operates in a high-touch environment. You will be evaluated on your ability to communicate complex technical concepts to non-technical stakeholders and vice versa. Expect to discuss how you handle difficult client situations, align conflicting priorities, and keep "aloof" or busy stakeholders engaged.

Domain Knowledge & Technical Aptitude While you do not need to be a coder, you must possess strong data literacy. Depending on the specific team (e.g., CSR, Implementation, R&D), you may face questions regarding data privacy, AI ethics, or sustainability reporting. You need to show that you understand the product you are managing.

Adaptability & Resilience The process at Dataiku can be rigorous and priorities may shift. Interviewers look for candidates who remain composed under pressure, can pivot quickly when business needs change, and maintain a positive, solution-oriented attitude during lengthy engagement cycles.

3. Interview Process Overview

The interview process for the Project Manager role at Dataiku is comprehensive and rigorous. Based on candidate data, you should expect a multi-stage process that can span 5 to 6 rounds over the course of 4 to 6 weeks. The company takes hiring seriously and aims to ensure a strong fit for both technical aptitude and cultural alignment.

You will typically begin with a screening call with a Talent Acquisition Manager to discuss your background and interest. If successful, you will move on to interviews with the Hiring Manager and potential peers. A defining feature of this process is the Case Study or Presentation round, which often requires significant preparation time (3+ hours). This stage is critical; it is where you demonstrate your practical skills in a simulated environment. Be prepared for a process that tests your endurance and commitment.

The timeline above illustrates a funnel that narrows significantly after the Hiring Manager screen. Use the time between the initial screens and the presentation round to research Dataiku’s product suite deeply. The final stages often involve meeting cross-functional partners or leadership to validate your strategic thinking and culture fit.

4. Deep Dive into Evaluation Areas

To succeed, you must prepare for specific evaluation themes that Dataiku prioritizes. Based on recent interview data, the following areas are critical:

Project Management Scenarios & Execution

This is the core of the interview. You need to show how you take a project from ambiguity to delivery. Interviewers will dig into your past experiences to see if you own your projects or just spectate.

Be ready to go over:

• Risk Management – How you identify roadblocks before they become critical issues.
• Resource Allocation – Managing constraints when teams are stretched thin.
• Methodology Selection – Why you chose Agile vs. Waterfall for a specific data project.

Example questions or scenarios:

• "Describe a project that was falling behind schedule. How did you identify the root cause and what steps did you take to recover?"
• "How do you handle scope creep when a client adds requirements mid-sprint?"

The Case Study Presentation

This is often the "make or break" round. You may be asked to prepare a presentation on a specific topic, such as a project launch plan or a strategic initiative.

Be ready to go over:

• Structure and Clarity – Your ability to synthesize information into a cohesive narrative.
• Strategic Thinking – Linking project tactics to broader business goals.
• Q&A Handling – Defending your choices during the presentation.

Example questions or scenarios:

• "Present a rollout plan for a new internal tool, including communication strategy and risk mitigation."
• "Analyze this hypothetical client scenario and propose a project roadmap."

Domain-Specific Knowledge (CSR / Data / AI)

Depending on the specific PM opening, you may face technical questions related to the domain. For example, recent candidates for specific PM tracks reported questions on Corporate Social Responsibility (CSR) and sustainability.

Be ready to go over:

• Data Lifecycle – Understanding how data moves from ingestion to visualization.
• Specialized Topics – Concepts like ESG (Environmental, Social, and Governance) reporting or AI Governance if relevant to the specific job description.

Example questions or scenarios:

• "How would you approach a project focused on improving our corporate social responsibility reporting?"
• "What are the key challenges in managing a data science project compared to software engineering?"

5. Key Responsibilities

As a Project Manager at Dataiku, your daily work revolves around bringing order to the dynamic world of AI implementation. You act as the connective tissue between the platform’s capabilities and the customer’s business objectives.

You will be responsible for end-to-end project delivery. This involves defining project scope, creating detailed work breakdown structures, and managing timelines in tools like Jira or Asana. You will frequently lead status meetings, ensuring that all stakeholders—from data scientists to executive sponsors—are aligned on progress and next steps.

Collaboration is central to this role. You will work closely with Customer Success Managers to ensure client satisfaction, Sales teams to understand initial promises, and R&D to provide feedback on product usage. In some roles, you may manage internal change management initiatives, helping Dataiku scale its own operations as the company grows. You are expected to be a proactive communicator who anticipates needs rather than waiting for instructions.

6. Role Requirements & Qualifications

To be competitive for this position, you need a blend of structured management skills and industry awareness.

• Experience Level – Typically requires 3–5+ years of experience in project management, preferably within a SaaS, software, or data consultancy environment.
• Technical Familiarity – You do not need to code, but you must be comfortable with technical terminology. Familiarity with Dataiku DSS, Python, R, or SQL concepts is a strong differentiator.
• Certifications – PMP, PRINCE2, or CSM certifications are often viewed favorably as evidence of formal training.
• Soft Skills – exceptional presentation skills are non-negotiable. You must be able to command a room and manage expectations with senior leadership.
• Language Skills – For roles based in specific regions (e.g., Paris), fluency in local languages plus English is often required.

Must-have skills:

• Proven experience managing complex, cross-functional projects.
• Proficiency with project management software (Jira, Monday.com, etc.).
• Strong grasp of the software development lifecycle (SDLC).

Nice-to-have skills:

• Background in Data Science or Analytics.
• Experience with CSR or ESG initiatives (for specific roles).
• Previous experience in a hyper-growth startup environment.

7. Common Interview Questions

The following questions are representative of what you might face at Dataiku. They are designed to test your behavioral patterns, your technical comfort, and your ability to structure your thoughts. Do not memorize answers; instead, prepare stories (using the STAR method) that highlight your adaptability and leadership.

Behavioral & Leadership

These questions assess how you work with others and handle adversity.

• "Tell me about a time you had to influence a stakeholder who disagreed with your approach."
• "Describe a situation where you had to deliver bad news to a client or manager. How did you handle it?"
• "How do you keep a team motivated during a long, difficult project?"

situational & Process

These questions test your practical application of PM methodologies.

• "If you join a project that is already delayed and over budget, what are your first three actions?"
• "How do you prioritize features or tasks when everything is labeled as 'high priority'?"
• "Walk me through your process for kicking off a new engagement with a client."

Domain & Technical

These questions ensure you can speak the language of the team.

• "How do you measure the success of a data project beyond just 'on time and on budget'?"
• "What is your understanding of Dataiku's position in the AI market?"
• "Can you explain a complex technical concept to me as if I were a five-year-old?"
• "What are the key components of a CSR strategy?" (For CSR-focused roles).

8. Frequently Asked Questions

Q: How difficult is the interview process? The process is generally rated as Medium to Hard. The difficulty often stems from the length of the process (5+ rounds) and the depth required in the presentation round. You should expect to be challenged on both your soft skills and your strategic thinking.

Q: Is the presentation round mandatory? Yes, for most Project Manager roles, a presentation or case study is a standard part of the loop. Candidates have reported spending significant time (3+ hours) preparing for this. It is your opportunity to showcase your work ethic and communication style.

Q: What is the work culture like for PMs? Dataiku values work-life balance (rated highly at 4.1/5) but expects high performance. The culture is collaborative and intellectual. However, some candidates have noted that you need to be self-driven, as management can sometimes be hands-off.

Q: Can I work remotely? Dataiku generally supports a hybrid model, though this varies by office location (e.g., New York, Paris). The role often requires real-time collaboration with teams, so being in a time zone aligned with your primary stakeholders is important.

9. Other General Tips

Invest in the Presentation Do not treat the presentation round lightly. This is the single most important artifact you will produce during the interview. Ensure your slides are polished, your narrative is compelling, and your data is accurate. Practice your timing to ensure you leave room for Q&A.

Drive the Conversation Some candidates have reported "aloof" interviewers or a lack of clear direction on next steps. Do not be passive. At the end of every interview, ask insightful questions about the team structure, current challenges, and the timeline. Show that you are a proactive communicator—a key trait for a PM.

Know the Product You don't need to be a Dataiku expert, but you should understand what DSS does. Read their whitepapers, watch a demo video, and understand who their competitors are (e.g., DataRobot, Alteryx). Mentioning specific product features in your answers shows genuine interest.

Prepare for "Changing Priorities" Be mentally prepared for a long process. There have been instances where roles were put on hold or priorities shifted during the interview cycle. patience and professional follow-up are essential.

10. Summary & Next Steps

Becoming a Project Manager at Dataiku is an opportunity to sit at the forefront of the AI revolution. You will be instrumental in helping organizations transform their data into actionable insights, working within a company known for its strong culture and innovative product. While the interview process is demanding—requiring endurance through multiple rounds and a rigorous presentation—it is designed to identify candidates who are truly ready to lead.

To succeed, focus your preparation on structured problem solving, stakeholder influence, and domain fluency. Review your past projects to identify clear examples of how you navigated risk and ambiguity. Treat the presentation round as a simulation of your actual work product, and bring high energy to every conversation.

The salary data provided above gives you a baseline for negotiation. Note that compensation at Dataiku typically includes a mix of base salary and equity (RSUs), and ranges can vary significantly based on location (e.g., New York vs. Paris) and seniority. Be prepared to discuss your expectations transparently with the recruiter early in the process.

You have the skills to navigate this process. Stay organized, be proactive, and demonstrate that you are the leader who can deliver results in a complex environment. Good luck!