Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate AI agents, analytics, and machine learning with the transparency, collaboration, and control enterprises require.
For more than a decade, Dataiku has helped organizations turn data, analytics, and AI into measurable business value. As the market has evolved from analytics to machine learning to generative AI and agents, Dataiku has enabled customers to stay ahead—operationalizing new technologies while maintaining stability, governance, and trust.
Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack, enabling organizations to run AI across multi-vendor environments with centralized governance and oversight, at scale.
Today, many of the world’s leading companies rely on Dataiku to deploy AI applications and agents in some of the most complex and highly regulated environments — turning AI into an enduring source of performance, competitive advantage, and long-term business value.
Rating Reviews
Rating is calculated based on
8
reviews and is evolving.
Pros: The AI and machine learning industry is booming, and Dataiku is at the forefront. I've learned a ton about enterprise AI deployments and working with complex datasets. The team is smart, collaborative, and genuinely interested in helping each other succeed. The hybrid work model offers good flexibility.
Cons: While pay is competitive, it might not be top-of-market compared to some Big Tech roles. Sometimes project priorities can shift unexpectedly, leading to a bit of churn. Communication from higher leadership could occasionally be more consistent regarding long-term strategy.
Advice to Management: Continue fostering cross-functional collaboration and be more transparent with strategic roadmaps to keep everyone aligned and motivated through growth phases.
Show more
Pros: The team I'm part of is fantastic, full of smart and supportive colleagues. Dataiku's platform itself is impressive, and being able to contribute to its development and support clients using it is very rewarding. There's a real sense of purpose, and the learning opportunities, especially in AI and ML, are abundant. Working in the SaaS industry here is exciting.
Cons: Sometimes the pace can feel very fast, which is exciting but can lead to longer hours when deadlines are tight, impacting work-life balance occasionally. Communication between different departments, especially between engineering and customer-facing teams, could be a bit smoother to ensure everyone is aligned on product roadmaps and client needs.
Advice to Management: Consider streamlining inter-departmental communication channels and look into ways to better manage project scope to prevent occasional work-life balance strains during peak periods.
Show more
Pros: I really enjoyed the collaborative spirit here. The teams I worked with, especially within the engineering and product departments, were incredibly supportive and smart. There's a genuine emphasis on learning and development, with plenty of internal resources and opportunities to pick up new skills in the AI/ML space. The product itself is impressive and serves a real need in the market.
Cons: While overall job security is decent given the market, sometimes there can be a lack of clarity around individual career progression paths. Middle management is generally good, but sometimes decisions or approvals can feel a bit slow, impacting project timelines. Workload can also ramp up significantly during crunch times, affecting work-life balance.
Advice to Management: Focus on creating more transparent career development frameworks for employees and streamlining internal processes to improve project velocity. Continued investment in employee learning is a big plus.
Show more
How long does it usually take to hear back after applying for a Data Scientist role at a mid-sized tech company like Dataiku?
For a Data Scientist position at Dataiku, I heard back about a week after applying; the whole hiring process for this large enterprise AI platform company felt efficient.
How does Dataiku help category managers escalate issues with large retail partners?
In my experience at a mid-sized CPG company, Dataiku's collaborative features let us quickly flag and track issues, speeding up resolution with our major retail clients.
As a CEO, how can I ensure my data science team using Dataiku trusts its outputs for strategic decisions in a mid-sized tech company?
I've found that empowering my team to document their workflows and build model monitoring within Dataiku really builds confidence in the results for critical business insights.
What's it like working as a data scientist at a mid-sized tech company using Dataiku?
Using Dataiku has been great for streamlining our workflows here; it really helps our data science team collaborate effectively on projects in the healthcare industry.
Yes, I work remotely for Dataiku from my home office in the US, which is great for work-life balance in the data science industry. Many roles in this growing tech company offer hybrid or full remote options.
What's it like using Dataiku for category management at a large CPG company?
Dataiku streamlines our category management workflows by connecting disparate data sources, allowing for faster insights and more agile decision-making for our product lines. It's been instrumental in optimizing our retail strategies.
Is Dataiku a good company for remote work in the AI industry?
Yes, Dataiku actively supports remote work for many roles, offering flexibility that's great for maintaining work-life balance within the fast-paced AI sector. I found their remote setup very effective for collaboration across different teams.
What's the typical interview process like for a Data Scientist role at a large enterprise using Dataiku?
My interview process for a Data Scientist position at a major financial services company involved a few stages, starting with an initial screening, followed by a technical assessment that included using Dataiku for a specific data analysis task, and concluding with behavioral interviews.
FR
