data
Added 2 weeks agoLead Data Scientist
at Populix
Jakarta, IndonesiaOn-site
Responsibilities
- Collaborate with the research and marketing teams to create simulation-driven whitepapers and internal studies, helping communicate the value of synthetic insight across use cases like campaign testing, segmentation, and hypothetical trends.
- Drive automation of research workflows that involve open-ended responses and audio data, including pipelines for transcription, classification, summarization, and sentiment analysis.
- Collaborate closely with engineers, designers, and product teams to ship robust ML-powered tools into production across the Populix platform.
- Lead the Design and implementation of behavioral simulation responses and demographic patterns using generative models, statistical modeling, and controlled simulations.
Requirements
- About the Role: Populix is building the future of AI-powered market research, combining structured data, unstructured insights, and generative AI into a seamless research intelligence platform.
- We're looking for a Lead Data Scientist to help drive that vision forward, someone who can spearhead the development of simulation systems and automation pipelines, while actively supporting the Head of Data Science in shaping our AI research strategy.
- You'll also play a key role in advancing our use of retrieval-augmented generation (RAG) and modular AI architectures to deliver insights that are fast, accurate, and contextualized. Key
- Help scale our AI insight engine by contributing to Retrieval-Augmented Generation (RAG) workflows and collaborating with LLM engineers on modular pipelines for context-rich output generation.
- Provide mentorship to other data scientists, sharing knowledge, reviewing modeling work, and helping maintain a culture of experimentation, reproducibility, and ethical AI. Required
- Qualifications: Master’s degree required, preferably in Computer Science, Statistics, Data Science, or a related quantitative field; PhD is a strong plus 5+ years of
- experience in data science or applied machine learning, including at least 1 year in a technical leadership role Deep
- experience in generative modeling (e.g., GANs, VAEs), simulation, or behavioral data modeling, with a strong grounding in statistics and hypothesis testing. Hands-on
- experience with Retrieval-Augmented Generation (RAG) architectures and knowledge integration with LLMs. Solid programming skills in Python and