Here are the values and culture Lazada Data Science lives by daily to fulfil our mission of using data to serve our buyers, sellers, and Lazadians. If this appeals to you, reach out to me!
3. What is culture?
§ A set of shared beliefs, values, and practices
- It shapes our behavior and interactions
- It defines who gets hired and rewarded
§ A great culture helps:
- Deliver our best work, both as individuals and a team
- Professional learning and growth in a safe, open environment
- Develop a great workplace by attracting and retaining amazing teammates
4. Our Mission
Use data to create positive impact and
improve lives of buyers, sellers, and Lazadians
We serve our buyers, sellers, and stakeholders—do what’s right for them
6. Ownership
§ You care intensely about users and sellers and do what’s best for them
§ You think and act like a founder, in Lazada’s best interest, even when it’s
against the popular opinion
§ You take care of problems, small and large, as you see them, and never
think “that’s not my job”
§ You have good judgement on trade-offs between quick MVPs and
strategic, sustainable long-term decisions
§ You thrive on freedom, trust, and responsibility, and discover and fix
issues without being told to do so
7. Collaboration
§ You contribute and provide support to the team, improving team outcomes
§ You engage with other functions to understand their view and problems, and
work together to develop solutions
§ You collaborate effectively with people of diverse backgrounds and cultures
§ You nurture and embrace differing perspectives to make better decisions
§ You make time to help teammates
§ You respect others and help create a sense of belonging
8. Communication
§ You proactively and transparently communicate progress, results, and
learnings (i.e., “mistakes”)
§ You listen well and seek to understand before responding
§ You adapt your communication to people who may not share your
knowledge so they understand you better
§ You initiate conversation to find out what’s going on in Lazada
§ You provide candid, timely feedback to the team so we can all improve
9. Innovation
§ You generate new ideas that prove useful and add value
§ You challenge assumptions and suggest better approaches
§ You are curious, learn rapidly, and make connections others miss
§ You effectively assimilate technology and data science advances and apply
them to our work
§ You thrive on change and view it as opportunity for improvement
10. Impact
§ You ship valuable work and accomplish amazing outcomes, often going
above and beyond
§ You are driven and set ambitious targets with aggressive deadlines
§ You demonstrate consistently strong performance the team can rely on
§ You focus on results and measure outcomes obsessively
§ You are the lynchpin that enables people around you to perform better,
contributing to team outcomes
12. Risks and “mistakes”
§ There are no mistakes, only learnings—nobody has ever been fired for
discovering opportunities to learn
§ In technology and data, the biggest threat over time is lack of
innovation—you have freedom and space to fail
§ We take risks and believe in rapid experimentation—fail fast, learn faster
§ “Failure is an option here. If things are not failing, you are not innovating
enough” – Elon Musk
§ Exception: We are strict on ethical, safety, and information security issues
13. Responsibility & Independence
§ Everyone should have a sense of responsibility to do the right thing—this
allows good, independent decision making, consulting upwards when unsure
- We set clear context so you have proper information to make great decisions
§ Leader’s job: Set context, empower, and be highly informed of happenings
- When something dumb occurs, its the leader that failed to set proper context
§ Aim: To be highly aligned and loosely coupled, so we can be fast and flexible
§ This deck sets the proper context so we can decide and behave responsibly
and independently
14. Hiring: Philosophy
§ Hiring well is the most important contribution to our success
- If we lower the bar, what is discussed here will stop working
§ We are looking for strong people that improve the talent pool
- They should either be better than us, or have the potential to
§ We value people who are proactive, independent, and driven
- They should be self-driven, with solid plans to achieve ambitious goals
§ We value “T-shaped” people
- Skilled at a broad set of valuable things and an expert in your field
- E.g., skilled in SQL, Spark, Python, ML, Communication, and expert in Graph
15. Hiring: Evaluating candidates
§ Some questions we ask ourselves:
- Would I want this person to be my boss?
- Would I learn a significant amount from him or her?
- What if this person went to work for our competition?
§ Beyond technical skills, we value initiative & collaboration:
- Proactively understanding and defining key problems, and solving them
- Communicating well with others in their terms (explain like I’m five)
- These matter far more than strong technical skills in narrow areas
16. Hiring: Q&A
§ “If the bar is this high, would I be hired today?”
- The answer might be no, but this is a good thing—we should celebrate because it
means we’re growing correctly!
- As long as you deliver impact, learn lots, and have fun, it doesn’t matter
§ “But I really want/need someone to help on this project!”
- Lowering the bar is a natural response when there’s lots to do—hiring someone,
anyone seems smarter than not hiring at all
- This is a big mistake and hurts the team in the long-term
17. Development & Growth
§ We develop our team by:
- Surrounding them with teammates they can learn from
- Giving them ambitious challenges to work on
§ We encourage you to be proactive in your professional development
- Don’t be shy—ask for help if you would like to develop in a certain area!
- Everyone has ownership over their growth and career path
§ You learn and grow professionally working on hard problems with
amazing teammates, as long as:
- We all try to help each other grow
- We are very honest with each other
18. Iterate, Iterate, Iterate
Feasibility assessment
§ Engage with
stakeholders to
clarify problem and
deliverables
§ Assess if problem
solvable with
current data
§ If not solvable,
move to backlog
and revisit
Proof of concept
§ Build basic proof-of concept to
assess if technically possible
§ Validate, either locally, or via AB
testing if possible
§ Continuously feedback results to
stakeholders to further refine until
satisfactory to use in production
Deploy to production
§ Engage with data engineers on
deployment best practices
§ Refactor code, if necessary, to
ensure scalability and robustness
§ Share with team via documentation,
code walkthroughs, etc.
Operational Maintenance
§ Fix critical issues as
necessary
§ Update if prioritized by
stakeholders