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Founder

Berdata

Berdata provides the latest information about data science and related fields with up-to-date blogs and educational material in Bahasa, Indonesia.

We also provide services to fulfill your data science and machine learning model needs, including:

- Data Analysis and Visualization
- Predictive Modeling and Machine Learning
- Business Intelligence (BI) Solutions
- Generative Artificial Intelligence and Deep Learning Solution Development
- Data Strategy and Consulting
- Optimization and Automation
- Training and Workshops

Arif Analytics

As the Lead Data Scientist and Startup co-founder, I oversee the data science team and steer the direction of the AI product. I will also collaborate with the other departments to ensure the AI product is on the right track.

My responsibilities including:
• Led the development of Data Science Dashboard features, including Data Visualization, Speech-to-Text, and Statistical Analysis, and enhanced the platform with LLM-powered Retrieval-Augmented Generation (RAG) and Agent capabilities
•Produce Product Requirements Document (PRD) and ensure the direction of AI product following the company vision.
•Managing the AI product usage and the cost incurred related to the AI activity.
•Collaborated with the team members to achieve target results and meet deadlines. Validate the timeline with the developer teams.

Lead Data Scientist (Generative AI/ LLM)

Stealth Startup

As an AI Engineer, I specialize in developing advanced AI products that leverage both open-source and closed-source LLM services. The product focuses on validating the business and connecting with the investor with AI.

My responsibilities including:
• Develop Financial-AI powered application with both open-source and closed-source LLM services.
• Implement AI models’ architecture and ensure the AI product met the company vision.
• Ensure AI models seamlessly integrated with the existing system.
• Translate the business requirement into necessary solution required from the application.

AI Engineer (Generative AI/ LLM)

KDnuggets

Contributing Writer

Allianz

•Generate Data Science end-to-end working framework for the company and implement MLOps design within the framework. End-to-end means from understanding the business problem to the model monitoring.

•Successfully implemented and supervised various Machine Learning model to improve the business quality, including:

    o Successfully implemented and supervised Propensity-to-Buy Machine Learning models in several business lines to meet the business target and achieved close to 150% of the Annual Target.
   o Develop a customer segmentation model and analyze the segment data to provide insight into actions suitable for each segment. The action insight is used to support the Propensity-to-Buy project.
   o Successfully implemented and supervised Churn Prediction Machine Learning models to avoid customer loss. Help decrease churn rate by 3%.
   o Technical Project Leader for Fraud Detection Model Project in 2024 that help improve claim fraud business pipeline.

•Leading teams of data scientist junior for the Machine Learning Project and educate the teams to be more independent

•Educate the company regarding the benefit of Data Science and Machine Learning to bridge the business and technical requirement

•Develop Microstrategy Business Intelligence Dashboard for Business User based on the Machine Learning project

•Implement the ML Cloud-Based Services AWS within the company, specifically for end-to-end data science use cases (In progress)

Data Scientist Assistant Manager (ML / LLM/ MLOps)

- Working day-to-day on the data project within the business to increase the business values of the company using the power of the data
- Harnessing the power of Machine Learning within the company department depends on the business user requirements. 
- Educate people for the AI and Machine Learning benefits to the Business user

Data Scientist Supervisor

Purwadhika Startup School

•	Successfully conducting a classroom session for Data Science Course with participants both from a professional industrial background (Banking, Finance, HR, Math, Marketing, etc.) and Fresh Graduate. 

•	Responsible for creating the Data Science teaching material and successfully implemented this material in the teaching session. Material including Python Programming Fundamental, SQL Fundamental, Data Science Analysis Methodology (Focus in Statistical Analysis and Visualization Analysis), and Machine Learning for Data Science. 
 
•	Responsible to supervise the social media analysis project. Currently in progress of the sentiment analysis project. Future project plan including customer segmentation analysis and forecasting.

Head of Data Science

Potentialpark

•	Auditing career website from a various company and provide feedback to the team leader
•	Gained experience in detail work and teamwork

Auditor

Department of Cell and Molecular Biology, BMC, Uppsala University

•	Assisting ongoing research by planning research plan, documenting research progress and analysing the research data
•	Establishing a Standard Operational Procedure for one of the research at the laboratory

Summer Research Assistant

Level up Your ML Game ❤️️| Writing a Lot | Data Mentor

🔹 I turn data into ROI for businesses by designing AI systems that solve high-impact problems—from fraud detection to customer retention. With 6+ years leading enterprise data science teams (like Allianz) and deploying LLM-powered tools, I bridge the gap between technical teams and business stakeholders.

🔹 I've written 500+ articles for platforms like KDNuggets, Machinelearningmastery, Towards Data Science, and Non-Brand Data (2M+ monthly readers), breaking down complex AI/ML concepts into actionable insights. My content isn't just theory—it's battle-tested from projects like:
✅ Propensity models that drove 150% of Allianz’s annual revenue targets
✅ Fraud detection systems reducing losses by 7-figure margins
✅ LLM chatbots with RAG that cut customer support costs by 30% 

🔹 Now, I help professionals and companies:

👉Consulting: Machine Learning Pipeline, LLM product design, and AI strategy.
👉Mentorship: Transition into data science careers via 1:1 coaching (100+ mentored since 2019).
👉Content: Partner with brands for technical articles, workshops, or whitepapers.

Let’s collaborate if you need:

📌A pragmatic AI consultant who ships code, not just slides.
📌A technical writer to simplify AI/ML for your audience.
📌A mentor to fast-track your data science career.

📩 DM me for consulting inquiries, mentorship slots, or content partnerships.

Cornellius Yudha Wijaya

•Context-Aware QA Chatbot: slashing client data retrieval time by 60% using 
Python, Langchain, and IBM Granite 3.2 LLM, integrating Elasticsearch for 
precise, data-driven answers from Proprietary datasets.
•Enterprise Scalability: End-to-End delivery (development through deployment) of 
scalable Generative AI and LLM solutions, customized to client workflows, 
demonstrably enhancing system performance and operational agility.
•Engineered autonomous AI agents using CrewAI and Llama 3.3, achieving a 40% improvement in decision making accuracy and response timeliness. Architected an intelligent framework that empowered the agent to dynamically select the optimal tool RAG for contextual data, a math tool for calculations, or real-time web search based on the user’s query. This multi-tool capability enabled robust, multi-step reasoning, allowing the agent to overcome base LLM limitations and deliver highly accurate, context-aware solutions.

AI Engineer

Thomson Reuters

•Developed all AI-driven Solutions in AWS cloud(Bedrock).
•GenAI Chatbot Development: Built and deployed AWS cloud-native (SageMaker, 
Bedrock) chatbots using Python, Langchain, and OpenAI (GPT-4 Turbo/GPT-4o), 
enhancing customer NPS score from 8 to 9 via transformer architectures and 
Advanced RAG.
•Enterprise Advanced AI Solutions: Engineered custom prompt workflows and 
Weaviate vector DB integration for optimized query processing, improving 
response accuracy by 25%+ using company-specific data.
•Customer feedback Insight Extraction: Leveraged NLP (Nltk) and LLMs to 
identify actionable pain points from unstructured text, driving data-backed 
product decisions.Leveraging this cutting-edge techniques to unlock hidden 
patterns and trends

Data Scientist

Convertcart

•Driven a 2% increase in overall sales and revenue by developing predictive 
models for customer engagement.
•Acquired and integrated datasets from multiple sources, performing rigorous 
Data Preprocessing to ensure data quality and accuracy.
•Conducted comprehensive Exploratory Data Analysis (EDA), Statistical Analysis, 
and Data Visualization to uncover key insights into customer behavior.
•Applied advanced Feature Selection techniques and Regression Modeling to 
build accurate predictive models for customer engagement scores.
•Implemented Unsupervised Learning (Customer Segmentation) to identify 
distinct customer groups, enabling targeted engagement strategies and 
optimized resource allocation.

Analyttica Datalab Inc.

•Developed and Dockerized deployment of an NLP solution using Python (NLTK, 
scikit-learn, TensorFlow) to automatically prioritize support tickets, significantly 
enhancing operational efficiency through Natural Language Processing.
•Delivered multi-million dollar cost savings and reduced ticket resolution time 
by 100 hours by accurately classifying priority issues using custom-built MLP 
models, demonstrating strong Predictive Modeling capabilities.
•Engineered robust end-to-end ML pipelines involving Text Preprocessing, 
Feature Engineering (word2vec, TF-IDF), and handling Imbalanced Data for 
Machine Learning model development.
•Implemented, evaluated (Model Evaluation), and optimized diverse ML algorithms 
(Logistic Regression, Decision Trees, Random Forest, Gradient Boosting) via 
Hyperparameter Tuning using Python (NumPy, pandas, scikit-learn).
•Managed the full MLOps cycle: instituted monthly model retraining, conducted 
A/B Testing for performance validation, and ensured continuous model 
monitoring in production using Deep Learning (TensorFlow) techniques.
•Proficiently presented technical solutions and impact analysis to stakeholder, 
translating complex Machine Learning technquies and Intelligent automation 
into business value (Stakeholder Communication)

AI Engineer @ IBM | 4 Yrs Exp. in ML, DL, DS, NLP, GenAI & Agentic AI | Ex-Thomson Reuters | VIT Alumni

Senior AI Engineer at IBM with a 4-years of track record of developing and deploying high-impact AI solutions. I thrive at the intersection of Machine Learning, Deep Learning, NLP, and the forefront of Generative AI. My toolkit includes Python, TensorFlow, Keras, and an advanced command of the modern NLP/GenAI ecosystem: LLMs, LangChain, RAG, prompt engineering, sophisticated fine-tuning, and vector databases,Tools,Agents.My analytical prowess is powered by Python (NumPy, Pandas, Matplotlib/Seaborn/Plotly), SQL, and robust data management practices. I am deeply passionate about pushing the boundaries of AI through continuous learning and creating innovative solutions.

taplio

The Battle

Cornellius Yudha Wijaya

Achutha Subhash

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