DataRaccoon

README!

A Work in progress document describing myself. Hopefully beneficial for you if you are my potential interviewer, interviewee or potential colleague!


Current Employment

Currently, I am the data lead for fraud and abuse in Traveloka. I cover all aspects from data science, analytics and engineering. I have, on multiple occasions put models into production as a tier 1/2 service within the organization either myself or via mentoring/leading my team.

Prior to leading fraud and abuse, I was the data lead and first data member for the financial technology arm and build the first iteration of the underwriting, fraud machine learning models for this lending product you see today.


Employment History

[Oct17-Present] Data Lead @ Traveloka (Fintech, Fraud, Abuse, Payments, Platform)

[Jun15-Oct17] Data Scientist @ Merck (Operations Research, Segmentation, Recommendation Engine)

[Jul14-May15] Data Trainee @ Google Squared (Google Analytics, Marketing optimization / Targetting)


Community involvement

I am also one of the main committee members behind the largest data science group - DSSG in Singapore with over 11k members at our Facebook group.

Do drop by and say hi if you attend our meetups!


Education

I graduated with a statistics degree in NTU under accelerated bachelors program. I also have minor in business, and scored a distinction in my final year thesis on Machine Learning as well as being placed on the deans list.

Currently no plans for graduate studies.


Resume

Here you go!


Extras


Top Negative feedback you should know

  • I am a direct individual, and sometimes i can speak my mind freely. If I accidentally offend you, I apologize, it is definitely unintentional. I am actively trying to work on this.
  • Resting Bitch Face =[ - Please give me a chance, I enjoy getting trolled (and trolling others), even at my own expense!

What do I value most?

  • Impact
    • How is your work attributed to the final results?
    • If you add/organize some structure, how much time do you save for others?
  • Difficulty / Complexity / ambiguity
    • How do you handle a tasks that is complex and difficult? are you able to break them down into pieces and solve them systematically?
    • In the event of an ambiguous problem, are you able to breakdown into valid suggestions, pros & cons on each suggestion and propose the next steps?
    • Sometimes what people say is not what they want, are you able to translate it for them for the metrics they actually care about?
  • Leadership/Initiative/Ownership
    • Do you help others when others are in difficulty? Do you make work easier for others?
    • If you see something is wrong, do you voice out and provide a helping hand?
    • If you have done something similar before, do you offer your expertise?

What do i not have patience for?

  • Does not practice what you preach, double standards.
  • Lack of growth mindset

How do I prefer to communicate and feedback

  • It is easy to miscommunication over text, face to face is usually preferred.
  • Feedback: I usually prefer to give/receive feedback on ad-hoc basis ,especially with (preferably recent) examples and concrete actionable, hopefully as recent as possible.
  • Crocker’s Law: I believe feedback is a gift and will not take offence.

What is my management perspective?

As long I can improve job opportunities for my team, everything else will fall in place. Better job opportunities means:

  • Better & more interesting work, challenges, opportunities
  • Which translates to better experiences, growth,
  • Then translates to better remunerations and happy colleagues.

Favorite Quotes

Success requires no apologies. Failure permits no alibis


Happiness = Reality - Expectations


Focus on signals over noise.


If you assign the wrong person to achieve the goal and suffer the consequences, it’s your fault, not the person who failed’s fault. So long as you bear the consequences of failure, you are the ultimate Responsible Party.

My personal quotes

Read at your own risk! Harsh content ahead!

My teammates / colleagues often suggest that I should put my momentary moments of brilliance online to share with the world, so, here goes!

You can have the best machine learning model, but if you cannot deploy it into production, it is no better than simple linear regression.


Every solution has a problem. If a solution has no problem, it would have been implemented yesterday!


Being kind to incompetency means being mean to the competent folks. Doing so breeds toxicity.


Growth at all cost? Are you sure? You know what grows the fastest? Cancer. Becareful.


North star metric? Ha, have you considered your South Star Metric? Focusing too much on your NSM can have unintended consequences.


If you want to do waterfall, do waterfall. If you want to do agile, please do agile. Never ever do agile waterfall (deadline is fixed but requirements keeps changing), because agile waterfall is equivalent to a tsunami, a disaster in the making!