Quantitative Modeler / Data Scientist

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Job Description: We are seeking a highly analytical and mathematically skilled Quantitative Modeler / Data Scientist to develop models that detect trend changes in time-series data using mathematical curve fitting, statistical analysis, and machine learning. The ideal candidate will work closely with engineering teams to turn raw data into actionable insights through custom-built mathematical models and real-time signal detection systems. ⸻ Responsibilities: • Analyze historical and real-time data to identify trends, patterns, and inflection points • Develop mathematical equations to fit time-series data (e.g., regression models, smoothing algorithms) • Implement trend detection algorithms to generate signals for upward/downward movement • Use derivatives or slope analysis to identify acceleration or deceleration of trends • Collaborate with engineers to deploy models into production environments • Visualize data and model outputs clearly for decision-makers • Continuously evaluate model performance and recalibrate based on new data ⸻ Qualifications: • Strong foundation in mathematics (calculus, statistics, linear algebra) • Proficient in Python, R, or MATLAB; familiar with libraries like NumPy, SciPy, pandas, scikit-learn • Experience with time-series analysis and signal processing • Prior experience with regression modeling, curve fitting, or forecasting techniques • Familiarity with financial markets or sensor/IoT data (depending on use case) • Ability to translate mathematical logic into code ⸻ Bonus Skills: • Experience with real-time data pipelines (Kafka, Redis, etc.) • Knowledge of algorithmic trading or anomaly detection

Keyword: Data Processing

Data Science Data Analysis Python Quantitative Analysis Statistics Statistical Analysis Machine Learning