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Samuel Chan

Analytics consultant at @supertypeai. Developer at @sectorsapp 📈. Instructor at @teamalgoritma

Samuel Chan is a prominent figure in the fields of Data Science, Machine Learning, BI / Data Visualization, Python, and R, with a strong presence on platforms like StackOverflow. He is recognized as a top expert in R in Indonesia and ranks in the top 5% worldwide on StackOverflow. Samuel was the first in Southeast Asia to obtain certifications in Microsoft's Data Science professional program and MongoDB. He has achieved the R tag badge on StackOverflow with a score exceeding 100 and is a certified RStudio trainer.

His extensive expertise spans Python, R, and full-stack development encompassing front-end technologies like jQuery, back-end technologies like Django, Flask, Shiny (R), and proficiency in PostgreSQL. Samuel is well-versed in Enterprise Business Intelligence software and is an open-source contributor collaborating on various projects. He specializes in developing data-heavy web applications, Python / R packages tailored for enterprise usage, and has also delivered guest lectures at universities.

Currently, Samuel is focusing on pedagogy endeavors, particularly in performance management for education professionals through open-source platforms like PedagogyApp and developing course production and automation tools via Corgi. He is actively involved in creating open-source command-line tools, web scrapers, visualization tools, and web app templates on GitHub under the moniker onlyphantom.

In his career journey, from 2006 to 2012, Samuel co-developed Malaysia's first student-centric network and forum, eventually selling a majority stake to a leading media conglomerate. He then ventured into product development for startups, utilizing modern web stacks such as MongoDB, SQL, NodeJS, and MVC architecture. Subsequently, Samuel implemented data-centric marketing processes for the TWP of DNP Group in 2012.

His career progressed to significant roles like heading marketing at Gumi Asia, where he established highly successful user acquisition models that generated substantial revenues daily, specifically for the title Brave Frontier. Samuel excelled in building competencies in data-driven publishing, fraud detection, and publishing operations within the organization. Later, from 2014 to 2017, he founded HyperGrowth, a company offering growth, automation, and anti-fraud solutions to advertisers. The company was headquartered in Singapore with offices in Jakarta and Vietnam, garnering investments from notable entities like SEGA-backed goVentures and Gunung Sewu.

Samuel also contributed to goGame as an Interim Head of Metrics Division, notable for titles like Disney Crossy Road, Big Hero 6, and Sonic the Hedgehog. He pioneered a marketing automation chatbot called GrowthBot.ai. Amidst his ventures, in 2017, Samuel focused on delivering premier data science education through Algoritma. He participated as a technical committee member and competition judge for Finhacks 2018, a prominent Machine Learning competition organized by PT. Bank Central Asia (BCA) and DailySocial. His authored courses are now offered by Ngee Ann Polytechnic in Singapore.

Highlights

Aug 29 · linkedin

August has been relentless!

First week was all production:

building Sectors, building the Generative AI for Finance lesson series (it’s freely available online, several chapters and continuously updated. Link in comment), building the materials for Enterprise Analytics, building learning solutions for our corporate clients.

7/8: Conducted the Enterprise Analytics 2024 workshop with Supertype

18/8 - 29/8: Spent ~10 days with the future data scientists and data professionals of PT Bank Rakyat Indonesia (Persero) Tbk on campus.

And add to that 3 flights 🛫🛬 in 3 week!

Documenting with all the photos from this month. Signing out on August!

Aug 25 · linkedin

Taken apart, each individual component of analytics are almost deceptively, simple (conceptually easy to reason). It's why hobby-level data science is fun.

But what isn't fun? Getting it to work on a large scale -- where the multiplicity of different systems having to work together begins to compound. Here's where that early enthusiasm quickly tapers off.

People like to blame corporate politics or change-resistance, and maybe it isn't entirely unfair. But the real problem is that the complexity of enterprise analytics is non-linear, and greater than the sum of its parts.

Everybody venturing into the field has to start somewhere, often times with a trivial implementation / individually-solved proof-of-concept.

But what's trivial individually becomes a cobbled-together mess when you have to make it work with other systems. The complexity isn't linear, but proof-of-concepts aren't generally forward-looking, nor are they supposed to be. They're isolated experiments unaware of the larger collective.

So no, it's not just corporate politics. The complexity of analytics is simply non-linear, and compounds in a matrix of different systems, in ways that can be unpredictable. Stop misappropriating blame, and do the work. (rant over)

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Samuel Chan
Samuel Chan, photo 1
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Location

Jakarta, Jakarta, Indonesia