You bring deep expertise in ML Ops and time-series forecasting to architect and implement scalable solutions on AWS. Key Responsibilities * Design, develop, and deploy machine learning models for ...
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You bring deep expertise in ML Ops and time-series forecasting to architect and implement scalable solutions on AWS. Key Responsibilities * Design, develop, and deploy machine learning models for ...
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Wilmer, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Wilmer, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Garland, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Garland, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Desoto, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Desoto, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
University Park, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
University Park, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Lancaster, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Lancaster, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Richardson, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Richardson, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Carrollton, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Carrollton, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Balch Springs, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Balch Springs, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Addison, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Addison, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Lead development of time series forecasting models (ARIMA, VAR, state-space models, etc.) for business-critical use cases. * Apply econometric techniques such as WLS, panel data models, and causal ...
Lead development of time series forecasting models (ARIMA, VAR, state-space models, etc.) for business-critical use cases. * Apply econometric techniques such as WLS, panel data models, and causal ...
Data Scientist
Cockrell Hill, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Cockrell Hill, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Hutchins, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Hutchins, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Farmers Branch, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Farmers Branch, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Desoto, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Desoto, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Mgr - Demand Forecasting and Demand Assurance
Morristown, NJ · On-site
$134K - $148K/yr
Develop and maintain time series forecasting models, incorporating machine learning algorithms and predictive analytics methodologies * Conduct in-depth data analysis and visualization of historical ...
Quick apply
Mgr - Demand Forecasting and Demand Assurance
Morristown, NJ · On-site
$134K - $148K/yr
Develop and maintain time series forecasting models, incorporating machine learning algorithms and predictive analytics methodologies * Conduct in-depth data analysis and visualization of historical ...
Data Scientist
Sunnyvale, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Data Scientist
Sunnyvale, TX · On-site
Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data processing.
Freelance Time Series Forecasting information
See salary details
$23.52 is the 25th percentile. Wages below this are outliers.
$14.90 - $25.57
31% of jobs
The median wage is $32.14 / hr.
$25.57 - $36.23
31% of jobs
$36.23 - $46.90
4% of jobs
$56.23 is the 75th percentile. Wages above this are outliers.
$46.90 - $57.56
10% of jobs
$57.56 - $68.23
9% of jobs
$68.23 - $78.89
5% of jobs
$78.89 - $89.55
0% of jobs
$89.55 - $100.22
8% of jobs
$100.22 - $110.88
0% of jobs
$110.88 - $121.55
0% of jobs
$121.55 - $132.21
1% of jobs
$14
$47
$132
How much do freelance time series forecasting jobs pay per hour?
As of Aug 22, 2026, the average hourly pay for freelance time series forecasting in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.
What is freelance time series forecasting?
Freelance time series forecasting involves independently analyzing and predicting future data points based on historical time-ordered data for clients or organizations. Freelancers in this field typically use statistical and machine learning methods to identify patterns and trends in data such as sales, stock prices, or weather. They may work on short-term projects or ongoing contracts, providing insights that help clients make informed business decisions. The flexibility of freelancing allows experts to work with various industries and datasets, often remotely.
What are the key skills and qualifications needed to thrive as a freelance time series forecaster, and why are they important?
To thrive as a Freelance Time Series Forecaster, you need a strong background in statistics, mathematics, and data analysis, often supported by a relevant degree and experience with forecasting methodologies. Proficiency in statistical programming languages (like Python or R), machine learning libraries (such as scikit-learn, statsmodels, or Prophet), and data visualization tools is typically required. Strong problem-solving skills, clear communication, and the ability to manage client relationships are crucial soft skills. These competencies enable accurate forecasting, effective project delivery, and successful collaboration with clients in data-driven environments.
What are some common challenges freelance time series forecasters face when working with clients?
Freelance time series forecasters often encounter challenges such as limited access to high-quality or complete datasets, which can impact the accuracy of their models. Communicating technical findings to clients with varying levels of statistical knowledge can also be demanding, requiring clear and actionable reporting. Additionally, managing multiple projects with different timelines and expectations requires strong organizational skills. Building trust with clients by explaining model limitations and providing transparent forecasts is key to long-term success in this role.
What is the difference between Freelance Time Series Forecasting vs Freelance Data Analyst?
| Aspect | Freelance Time Series Forecasting | Freelance Data Analyst |
|---|---|---|
| Credentials | Statistical, data analysis, or domain-specific certifications | Data analysis, statistics, or related certifications |
| Work Environment | Remote, project-based, often specialized in forecasting models | Remote or on-site, broader data analysis tasks across industries |
| Industry Usage | Finance, supply chain, sales forecasting | Marketing, operations, business intelligence |
| Search & Comparison Intent | Focus on predictive modeling and forecasting skills | Broader data analysis and reporting skills |
Freelance Time Series Forecasting specialists focus on creating models to predict future data points, often in finance or supply chain contexts. Freelance Data Analysts handle a wider range of data tasks, including reporting and insights. While both roles require analytical skills, forecasting is more specialized in predictive modeling, whereas data analysis covers broader data interpretation.
More about Freelance Time Series Forecasting jobs
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Cities with the most Freelance Time Series Forecasting job openings:
What are the most commonly searched types of Time Series Forecasting jobs?
The most popular types of Time Series Forecasting jobs are:
What states have the most Freelance Time Series Forecasting jobs?
States with the most job openings for Freelance Time Series Forecasting jobs include:
What job categories do people searching Freelance Time Series Forecasting jobs look for?
The top searched job categories for Freelance Time Series Forecasting jobs are:
Contractor
Posted 14 days ago
Job description
Role: Principal Consultant — AI/ML
Location - Houston, TX (Hybrid, Needs to be able to travel to Houston every other week)
Role Summary
As a Senior Consultant (L6), you are an experienced individual contributor who independently drives one or more AI/ML workstreams end-to-end. You own delivery outcomes for your assigned workstream, make key technical decisions, and interface directly with customer technical leads and stakeholders. You mentor L4 (Associate) and L5 (Staff) consultants on the team, providing technical guidance and reviewing their deliverables. You bring deep expertise in ML Ops and time-series forecasting to architect and implement scalable solutions on AWS.
Key Responsibilities
- Design, develop, and deploy machine learning models for latent capacity prediction across pipeline systems (weather, gas turbine HP, compressor flow, line pack, equipment performance)
- Build and maintain ML Ops infrastructure on AWS SageMaker including model registry, versioning, CI/CD pipelines, and multi-environment endpoints (Dev, Pre-Prod, Prod)
- Conduct exploratory data analysis and feature engineering for time-series forecasting of pipeline operational data (SCADA, performance curves, hydraulic models)
- Develop ensemble model strategies combining LSTM, Prophet, and XGBoost for improved prediction accuracy of latent capacity
- Build automated model deployment workflows, training/evaluation pipelines, and retraining frameworks
- Design real-time and batch inference architectures with API Gateway integration and model monitoring
- Collaborate with data engineering team on feature stores and data pipeline integration from Bronze/Silver/Gold data lakehouse layers
- Support hydraulic model integration with NextGen software for automated scenario generation
- Independently own delivery of assigned ML workstream, driving technical decisions and ensuring quality
- Mentor L4/L5 team members on ML best practices, code reviews, and architectural patterns
- Interface directly with customer technical leads to align on requirements, review progress, and resolve technical blockers
Required Skills & Qualifications
- Strong experience with AWS SageMaker, including SageMaker Pipelines, Model Registry, and Feature Store
- Proficiency in time-series forecasting (LSTM, Prophet, XGBoost, ensemble methods)
- Experience with ML Ops practices: CI/CD for ML, model monitoring, automated retraining
- Python (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch)
- Experience with real-time and batch inference architectures
- Knowledge of data lakehouse architectures (S3, Glue, Redshift)
- Understanding of industrial/operational data (SCADA, IoT sensors) is a plus
- Experience in Energy & Utilities domain preferred
- Demonstrated ability to independently lead technical workstreams and make architectural decisions
- Experience mentoring junior engineers or consultants
- Strong communication skills for customer-facing interactions