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Seasonal Graduate Machine Learning Jobs in Texas

Machine Learning Engineer - NJ

Addison, TX ยท On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

Machine Learning Engineer - NJ

Addison, TX ยท On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

Senior Machine Learning Engineer

Austin, TX ยท On-site

$121K - $160K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

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Seasonal Graduate Machine Learning information

What is the difference between Seasonal Graduate Machine Learning vs Data Analyst?

AspectSeasonal Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; knowledge of ML frameworksDegree in Statistics, Mathematics, or related field; proficiency in data visualization tools
Work EnvironmentTech companies, research labs, or industries applying ML models seasonallyBusiness environments, finance, marketing, or healthcare sectors
Employer & Industry UsageUsed in industries deploying ML solutions seasonally, such as retail or e-commerceCommon in industries analyzing data trends for decision-making

Seasonal Graduate Machine Learning roles focus on developing and applying machine learning models during specific seasons, often requiring programming and ML knowledge. Data Analysts interpret data to inform business decisions, emphasizing statistical analysis and visualization. While both roles involve working with data, Machine Learning positions are more technical and model-driven, whereas Data Analysts focus on insights and reporting.

What are the most commonly searched types of Graduate Machine Learning jobs in Texas? The most popular types of Graduate Machine Learning jobs in Texas are:

Machine Learning Engineer - NJ

Photon

Addison, TX โ€ข On-site

$54 - $71.50/hr

Full-time

Re-posted 21 days ago


Job description


Summary:
We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and engineering teams to solve complex business problems, identify data-driven opportunities, and create personalized experiences for customers. You will be responsible for building end-to-end machine learning solutions, implementing models in production, and working with various data frameworks and tools such as Python, Spark, and Databricks.
Key Responsibilities: Analytics Model Development:
  • Analyze use cases and design appropriate analytics models using statistical and machine learning algorithms tailored to specific business requirements.
  • Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights.
  • Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection.

Data Engineering and Preparation:
  • Extend and augment company data with third-party data to enrich analytics capabilities.
  • Enhance data collection procedures to include necessary information for building analytics systems.
  • Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing data formats using Python data frameworks (e.g., Pandas, NumPy).

Machine Learning Model Implementation:
  • Implement machine learning models, considering both performance and scalability using tools like PySpark in Databricks.
  • Design and build infrastructure to facilitate large-scale data analytics and experimentation.
  • Work with tools like Jupyter Notebooks for data exploration and model development.

What We're Looking For:
  • Educational Background: Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A PhD is preferred but not necessary.
  • Experience:
    • At least 5 years of experience in data analytics, with a strong understanding of core statistical algorithms such as classification and regression analysis.
    • High-level knowledge of analytics use cases such as language analysis, assortment optimization, promotional planning, dynamic pricing, markdown optimization, labor scheduling, and optimization.
  • Technical Skills:
    • Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
    • Proficiency in using analytics platforms like Databricks for large-scale data processing.
    • At least 4 years of continuous experience with Spark, particularly PySpark implementation.
    • Hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.