I Turn Data Into
Business Results.
I'm Aryanto, M.Si, a Senior Data Scientist and MLOps Architect with over 9 years of experience translating complex data challenges into tangible business ROI. I design and deploy production-grade machine learning systems and high-performance data architectures that directly drive revenue growth, minimize operational latency, and optimize cost-efficiency.
Throughout my career, spanning technical leadership and engineering roles at firms like Asia Pulp & Paper, AmTrust Mobile Solutions, and Electric Vine Industries, I have built high-impact recommendation systems, natural language processing (NLP) pipelines, and robust predictive engines. My approach bypasses standard slower libraries in favor of high-performance tools like Rust, Julia, C, Cython or in python such as module Cuda, Polars and DuckDB to ensure data pipelines execute with maximum throughput and minimum latency.
I specialize in bridging the gap between experimental models and enterprise-scale production environments. By combining rigorous MLOps infrastructure with optimized AI/ML algorithms (such as XGBoost and LightGBM for Learning to Rank models), I deliver robust, auto-scaling systems that remain resilient and highly performant under real-world workloads.
- Years Building ML
- 9+
- Since 2015
- Industries Served
- 10+
- Cross-domain expertise
- People Mentored
- 15+
- Growing data teams
- LinkedIn Recs
- 20+
- Verified endorsements
My Mission
I believe every sitting on data, customer transactions, operational logs, sensor readings, support tickets, is sitting on unrealized revenue. The challenge isn't having data. It's having someone who can turn that data into decisions.
My goal is simple: help businesses grow by making their data work harder. That means building recommendation engines that increase cross-sell revenue. It means deploying computer vision systems that automate manual inspections. It means creating NLP pipelines that turn thousands of customer feedback into actionable insights. And it means doing all of this in production, not in a Jupyter notebook that nobody opens after the project ends.
I don't just build models. I build the infrastructure, monitoring, and documentation that makes those models reliable, maintainable, and valuable over the long term. Because a model that degrades silently is worse than no model at all.
My Journey
From building data systems from scratch to leading data science teams across industries.
Started in Data
Began as a Data Analyst, building survey data management systems and reporting pipelines from scratch at an agribusiness firm in Indonesia.
Quantitative Risk & Actuarial
Moved into quantitative risk analysis at PT LAPI ITB, applying statistical modeling and actuarial methods to real-world business problems.
Data Science in Forestry
Joined Asia Pulp & Paper (Sinarmas) as a Data Scientist. Built precision forestry models using satellite imagery and geospatial analysis, one of the most technically challenging projects of my career.
Leading Data Science Teams
Promoted to lead data science at Merkle Indonesia (dentsu). Managing teams, mentoring junior scientists, and delivering ML solutions across automotive, telco, banking, insurance, and e-commerce.
Global Remote Consulting
Started independent consulting through Upwork and direct engagements. Working with clients across Asia, the Middle East, and Europe on recommendation engines, MLOps, and conversational AI.
Solo Principal Consultant
Operating as an independent contractor, no agency, no junior handoffs. Direct access to the person writing the code and building the models.
What I Stand For
Principles that guide every project I take on.
Production Over Perfection
A model that sits in a notebook is worthless. I build systems that deploy, monitor, and deliver measurable business impact. If it can't go to production, I won't build it.
Honest Communication
I tell clients what they need to hear, not what they want to hear. If a problem doesn't need ML, I'll say so. If a timeline is unrealistic, I'll flag it upfront. Trust is built on honesty.
Business-First Thinking
Every technical decision maps to a business KPI. CTR lift, conversion rate, automation hours saved, latency reduction, I measure success in outcomes, not accuracy scores.
Craftsmanship in Code
Clean, documented, tested code. Not because it's fancy, because the next person maintaining this system might not be me, and they deserve to understand what I built.
Beyond the Code
When I'm not building ML pipelines, I'm mentoring the next generation of data scientists. I've guided 15+ team members across multiple organizations, helping them write cleaner Python, structure better SQL queries, and think about problems from a business perspective, not just a technical one.
I believe strongly in documentation and knowledge sharing. Every system I build comes with architecture diagrams, runbooks, and handoff guides, because the best code in the world is useless if nobody else can maintain it.
I'm also a strong advocate for remote work. I've delivered projects across multiple time zones and continents, and my clients consistently note that responsiveness and reliability aren't compromised by distance.
"You can always contact him anytime and he will respond promptly as well as deliver the work on time!"
— Kurniawan Hakim, Data and CRM Leader at Merkle Inc.
Let's Work Together
Whether you need a recommendation engine, a computer vision pipeline, or strategic data science leadership, I'd love to hear about your project.