Senior Time Series Decomposition Expert (Remote)

Thrive League Africa; Abu Dhabi; Remote; AED 300,000 - 540,000; Full time

Benefits offered by this job

Remote work

Professional development

International teams

Competitive pay

Job summary

Thrive League Africa is seeking a Senior Time Series Decomposition Specialist to analyze complex time-dependent datasets, decomposing them into trend, seasonal, cyclical, and irregular components. The role is fully remote and requires strong statistical expertise, programming skills, and the ability to communicate findings to stakeholders.

You will design and validate decomposition methodologies, apply techniques like STL and X-13ARIMA-SEATS, and integrate outputs into forecasting and anomaly

Qualifications

• Extensive experience in time series analysis and forecasting.
• Proficient in decomposition methods and residual diagnostics.
• Strong programming skills in Python or R.

Responsibilities

• Design and implement time series decomposition methodologies for diverse datasets.
• Separate observations into trend, seasonal, cyclical, and residual components.
• Apply decomposition techniques such as STL and X-13ARIMA-SEATS.
• Evaluate stationarity, autocorrelation, and model assumptions.
• Integrate decomposition outputs into forecasting and anomaly detection workflows.
• Prepare technical reports and visualizations for stakeholders.

Skills

Time series analysis

STL decomposition

X-13ARIMA-SEATS

Forecasting

Statistics

Python

R

SQL

Data visualization

Communication

Education

Bachelor's or Master's in Statistics/Data Science/Econometrics

Tools

SQL

ARIMA

STL

Job description

Thrive League Africa is seeking a Senior Time Series Decomposition Specialist to analyze complex time-dependent datasets, decomposing them into trend, seasonal, cyclical, and irregular components. The role is fully remote and requires strong statistical expertise, programming skills, and the ability to communicate findings to stakeholders.

You will design and validate decomposition methodologies, apply techniques like STL and X-13ARIMA-SEATS, and integrate outputs into forecasting and anomaly