Machine Learning & Time Series Forecasting

Job Title: Machine Learning & Time Series Forecasting Specialist

Location: Remote – Latin America 

Type of Contract: Full-Time

Salary Range: Market Rates

Language Requirements: English fluency required

We are seeking a skilled Machine Learning & Time Series Forecasting Specialist with strong expertise in data modeling and predictive analytics to join our growing team. You will play a key role in building and optimizing models to forecast business trends and support strategic decision-making. Your work will directly impact operational efficiency, planning accuracy, and revenue growth.

Key Responsibilities:

• Develop and implement machine learning models for time series forecasting across business use cases

• Analyze large datasets to extract insights and identify patterns using Python, R, or similar tools

• Build, test, and validate forecasting models using ARIMA, Prophet, LSTM, and other time series techniques

• Collaborate with data engineers and business analysts to deploy scalable, production-ready solutions

• Continuously improve model performance through feature engineering, tuning, and evaluation

• Present results and model findings to non-technical stakeholders through clear visualizations and reports

• Maintain documentation and contribute to best practices for forecasting processes

Must-Have Qualifications:

• 3+ years of experience in machine learning with a focus on time series forecasting

• Proficiency in Python (Pandas, NumPy, scikit-learn) and time series libraries (Prophet, statsmodels, etc.)

• Strong understanding of statistical modeling and forecasting techniques

• Experience working with real-world, noisy datasets

• Familiarity with cloud platforms (AWS, GCP, or Azure) and version control tools (Git)

• Solid communication skills and ability to explain complex concepts to cross-functional teams

• Bachelors degree in Computer Science, Statistics, Mathematics, or a related field

Preferred Qualifications:

• Experience with deep learning models for forecasting (e.g., LSTM, Transformer-based models)

• Background in demand forecasting, financial modeling, or supply chain analytics

• Masters degree in a quantitative field