Bandung
Rp8 jt – Rp12 jt18 hari lalu
to design, build, and deploy an autonomous AI agent capable of scraping complex time-series price data and generating actionable predictive insights. You will bridge the gap between robust data engineering and advanced predictive modeling, leveraging modern agentic workflows to accelerate the development and deployment of this system.
Key Responsibilities
Design and implement an autonomous agent capable of scraping, cleaning, and normalizing high-frequency time-series data from various sources (APIs, web scraping, or direct data feeds).
Develop and train time-series forecasting models (e.g., LSTM, GRU, Transformers, or statistical models like ARIMA/Prophet) to generate accurate price predictions.
Build scalable, reliable pipelines that ensure the continuous flow of data from ingestion to model inference.
Monitor model performance, iterate on feature engineering, and refine scraping logic to handle site anti-bot measures and data latency.
Proficiency in web scraping tools (Playwright, Selenium, BeautifulSoup, or Scrapy) and working with time-series databases (e.g., InfluxDB, TimescaleDB, or ClickHouse).
Agentic IDEs & Tools
: Hands-on experience with AI-native development environments and agentic coding tools (e.g., AWS Kiro, Cursor, or GitHub Copilot Agent mode) for specification-driven development, automated task decomposition, and code generation.
Familiarity with orchestration frameworks (e.g., LangChain, CrewAI, or AutoGen) for managing autonomous agent workflows.
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