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Assistant Data Scientist Forecasting Jobs in Texas

TX · On-site

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Experience in time-series forecasting, causal inference, feature engineering, and advanced data ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Data Scientist Location: Houston, TX (Fulltime) Environment: Standard, 5-days onsite : Must-Have ... Shipping cost forecasting * Gas network disruption analysis * Create data visualizations for both ...

Structured Data (80-90%) - Predictive analytics, forecasting, cost estimation, likelihood modeling ... Ability to write clean, optimized code and leverage AI code assistants. ✅ NLP / GenAI Specific ...

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ...

Senior Data Scientist

San Antonio, TX · On-site

$140 - $210/hr

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ...

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ...

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis ...

Showing results 21-40

Assistant Data Scientist Forecasting information

What does an assistant data scientist forecasting do?

An Assistant Data Scientist in Forecasting helps analyze historical data and uses statistical models or machine learning techniques to predict future trends or outcomes. Their tasks often include data cleaning, exploratory analysis, feature engineering, and supporting the development and validation of forecasting models. They work under the guidance of more experienced data scientists and may also help communicate results to stakeholders. This role is essential for businesses looking to make data-driven decisions about sales, inventory, demand, or other key metrics.

What are the key skills and qualifications needed to thrive as an assistant data scientist forecasting?

To thrive as an Assistant Data Scientist Forecasting, you need a solid foundation in statistics, data analysis, and forecasting methods, typically supported by a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with tools like Python, R, SQL, and forecasting libraries (e.g., Prophet, ARIMA), as well as experience with data visualization platforms, is essential. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex results and present actionable insights. These competencies are crucial to generate accurate forecasts that guide business decisions and drive organizational success.

What are some typical challenges assistant data scientists face when working on forecasting projects?

Assistant Data Scientists in forecasting often encounter challenges such as handling incomplete or noisy datasets, selecting appropriate modeling techniques, and tuning models for accuracy. They may also need to balance competing priorities between speed and precision, especially when deadlines are tight. Close collaboration with senior data scientists and domain experts is common, as it helps ensure that forecasts are both technically sound and aligned with business goals. Developing strong communication skills is essential for presenting complex findings to non-technical stakeholders.

What is the difference between Assistant Data Scientist Forecasting vs Data Scientist Forecasting?

AspectAssistant Data Scientist ForecastingData Scientist Forecasting
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles may prefer a master'sMaster's or PhD in Data Science, Statistics, or related field; strong programming skills
Work EnvironmentSupportive team, entry to mid-level projects, supervised tasksIndependent project work, complex analysis, strategic decision-making
Employer & Industry UsageTech companies, finance, retail, healthcare; entry to mid-level rolesResearch institutions, large corporations, specialized analytics teams

The Assistant Data Scientist Forecasting role typically involves supporting forecasting projects under supervision, focusing on data preparation and basic modeling. In contrast, a Data Scientist Forecasting leads complex forecasting models, interprets results, and influences strategic decisions. The roles differ mainly in experience level, scope of responsibilities, and independence.

What are the most commonly searched types of Data Scientist Forecasting jobs in Texas?

The most popular types of Data Scientist Forecasting jobs in Texas are:

What cities in Texas are hiring for Assistant Data Scientist Forecasting jobs?

Cities in Texas with the most Assistant Data Scientist Forecasting job openings:

Full-time

Posted 13 days ago


Job description

Required Skills
  • 10+ years of hands-on experience in Applied Data Science, Analytics Engineering, and Systems Modeling.
  • 5+ years of client-facing, consulting, or business development experience delivering analytics solutions.
  • Expertise in statistical modeling, machine learning, and predictive analytics.
  • Strong proficiency with Python, scikit-learn, statsmodels, PyTorch, and TensorFlow.
  • Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques.
  • Strong expertise in geospatial analytics and LiDAR data processing.
  • Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries.
  • Experience working with vector, raster, point-cloud, and sensor datasets.
  • Excellent analytical, communication, and stakeholder management skills.
Roles & Responsibilities
  • Design and develop advanced machine learning and statistical models to solve complex business problems.
  • Build predictive models, time-series forecasting solutions, and causal inference frameworks.
  • Perform feature engineering, data preparation, and advanced sampling techniques for large-scale datasets.
  • Develop geospatial analytics and LiDAR processing solutions using industry-standard tools and libraries.
  • Analyze vector, raster, point-cloud, and sensor data to generate actionable insights.
  • Partner with business stakeholders to scope, design, and deliver data science solutions.
  • Present analytical findings and recommendations to technical and business audiences.
  • Optimize model performance, scalability, and deployment in production environments.
  • Mentor data scientists and promote best practices in analytics and machine learning.
  • Support innovation initiatives through advanced analytics and AI-driven solutions.