Tiger Analytics is a data science and AI consultancy that delivers analytics, machine learning and data engineering solutions for enterprises across retail, financial services, healthcare and technology sectors. Headquartered in Menlo Park with a str...
"I enjoy the problem-solving focus here — you will get to work on interesting data problems," says a senior data scientist. Another colleague shares, "The teams are collaborative and you’ll learn fast, but sometimes client deadlines make things hectic." Newer hires often comment on the strong onboarding and mentorship, while some mid-level employees mention that project switches can be abrupt. Overall, testimonials paint a picture of a learning-centric workplace with a consultancy pace.
company culture at Tiger Analytics leans heavily toward curiosity and continuous improvement. The workplace values technical excellence, pragmatic solutions, and client-first thinking. People tend to be collaborative and open to sharing knowledge. There is an emphasis on merit — contributors who produce results are noticed. At the same time, the culture is typical of consulting shops: performance orientation combined with tight timelines. Socially, teams are friendly and inclusive, with cross-functional interactions across analytics, engineering, and business teams.
Feedback around work-life balance at Tiger Analytics is mixed. Many employees appreciate the flexibility and the option to work remotely or in hybrid mode, which helps balance personal commitments. At the same time, during project deadlines or client launches you will encounter long nights and weekend work. Overall, work-life balance at Tiger Analytics depends a lot on the role and the project cycle: client-facing and delivery roles will see more intensity than internal product or research roles.
There is a steady demand for analytics and AI services which supports job stability. Project-based work introduces some variability, but most employees report that core teams are well-supported and there are internal opportunities to move across projects. There is a structured approach to staffing and reallocation, so you will generally find options if your current project winds down. Major, unexpected layoffs are not commonly reported.
Leadership emphasizes technical credibility and client delivery. Senior leaders are visible in town halls and client pitches, and they invest in strategy and growth. There is a clear focus on scaling capabilities and building repeatable solutions. Management practices are generally professional: goal-setting, performance reviews, and business updates are regular. Communication from the top is often candid, though some employees feel more transparency could help during transitions.
Manager experiences vary by team. Many managers are praised for being supportive, technically sound, and willing to invest in team development. They often provide mentorship and clear feedback. However, in a few teams, managers are reported to be more delivery-focused with less time for career coaching. Overall, you will likely find approachable managers who care about project outcomes, but the level of regular one-on-one coaching can differ.
Learning & development is a strong suit. There are internal training programs, bootcamps for new tools, and regular tech talks. Employees report access to online courses, certifications, and a culture that rewards upskilling. The firm encourages engineers and data scientists to learn new methods, experiment with models, and publish internally. For someone who values growth, working at Tiger Analytics offers structured and on-the-job learning opportunities.
Promotion paths are defined and tied to performance, impact, and client delivery. Advancement timelines are typical for consulting firms: consistent high performers may move up in 12–24 months, while others follow a regular review cycle. Opportunities for promotions exist, especially for those who lead client engagements, contribute to IP, or mentor others. Competition is present, so proactive ownership of projects and visibility matter.
Compensation varies by role, location, and experience. As a rough guide:
There are performance bonuses tied to individual and company performance, along with spot awards and recognition programs. Bonus structures are usually transparent during reviews and tied to project outcomes and company profitability. Incentives for business development, client wins, or exceptional contributions are common.
Health coverage typically includes standard medical insurance for employees and, in many locales, family coverage options. Additional benefits often include life insurance, accidental cover, and employee assistance programs for mental health. Wellness initiatives and preventive care benefits are available in most locations. Specifics vary by country and local policies.
Engagement is active: hackathons, internal demo days, learning weeks, and team outings are regular. Town halls and Q&A sessions with leadership keep employees connected. Social events and interest groups (data science clubs, reading circles) help build community. Employee engagement is treated as an ongoing priority.
Remote work support is solid: collaboration tools, cloud access, and remote onboarding are well-established. The company supports hybrid and fully remote roles depending on client needs. Equipment reimbursement and home-office support are available in many locations. Remote collaboration is smooth for most technical teams.
Average working hours reflect consultancy norms. Typical weeks are around 40–45 hours, but peak periods can push that to 50+ hours. Timing depends on project schedules and client time zones. Predictability improves in internal or research-focused roles.
Attrition is moderate, in line with the analytics consulting industry, driven by competitive market demand for data talent. Staff turnover is driven by growth opportunities elsewhere and project cycles rather than major restructuring. There is no widespread pattern of frequent mass layoffs reported; role realignments happen occasionally as projects change.
Overall, this company earns a positive rating for people who value learning, technical challenge, and client-facing work. It combines a collaborative culture with solid L&D and reasonable benefits. Prospective employees should be comfortable with the variable pace of consulting and be proactive about career visibility. A fair overall rating would be 3.8 out of 5: strong on growth and technical exposure, slightly variable on work-life predictability and manager consistency. If you are considering working at Tiger Analytics, expect an engaging, growth-oriented environment with occasional high-intensity stretches.
Read authentic experiences from current and former employees at Tiger Analytics
Good exposure to real problems.
Long hours and sometimes unclear priorities. On-site requirement felt strict for junior roles. Salary is lower than market.
Great clients, supportive leadership.
Resource crunch at times. Communication between global teams can be uneven which impacts timelines and clarity.
Supportive manager, great mentorship and lots of hands-on ML work. Tiger Analytics gives access to varied industries which accelerates learning.
Compensation could be improved; occasional sprint crunches before delivery.
