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Machine Learning Jobs in Chesterfield, MO (NOW HIRING)

Responsibilities - Leading the design and development of AI and Machine Learning solutions to transform raw data into actionable insights - Overseeing the implementation of data infrastructure and ...

As an Expert Data Scientist at Nestle Purina,you'llsupport enterprise-wide AI and machine learning use case creation, deployment, and operationalization across critical business initiatives that ...

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Develop and deploy machine learning, statistical, and optimization models that solve business problems and improve operational performance * Support the development and maintenance of optimization ...

You will be helping create high-quality products that support children's learning and development ... Operate industrial sewing machines to assemble fabric pieces according to patterns, sew notes ...

Machine Operator

Sauget, IL

$16.50 - $19.75/hr

We're committed to making a positive impact on the world, providing you with diverse learning and ... General Labor, Machine Operator, Maker/Packer, Assembler and Line Operator. Location: Sauget, IL ...

New

Solid traditional Machine Learning: Feature engineering, model training, evaluation * Not a model-only / AI-heavy DS * Less focus on deep learning, GenAI, etc. * More focus on data foundations ...

Showing results 41-60

Machine Learning information

See Chesterfield, MO salary details

$25.2K

$42.1K

$87.1K

How much do machine learning jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning in Chesterfield, MO is $42,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,500.00 per year, depending on experience, location, and employer.

What is a machine learning?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are the typical day-to-day responsibilities in a machine learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With a background in machine learning, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These positions typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive in a machine learning position?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

What are popular job titles related to Machine Learning jobs in Chesterfield, MO? For Machine Learning jobs in Chesterfield, MO, the most frequently searched job titles are:
What cities near Chesterfield, MO are hiring for Machine Learning jobs? Cities near Chesterfield, MO with the most Machine Learning job openings:
Infographic showing various Machine Learning job openings in Chesterfield, MO as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $42,147 per year, or $20.3 per hour.

Senior Data Scientist

Tiger Analytics Inc.

Saint Louis, MO • On-site

Full-time

Re-posted yesterday


Job description

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As a Data Scientist you will be at the forefront of solving high-impact business problems using advanced machine learning, data engineering, and analytics solutions. The role demands a balanced mix of technical expertise, stakeholder management. You will design and analyze A/B tests and apply advanced techniques such as causal inference, matching models, and AutoML to generate reliable, actionable insights. Partnering closely with business and cross-functional teams, you will translate hypotheses into robust analytical models, validate outcomes with statistical rigor, and clearly communicate results to drive data-backed decision-making and measurable business value.

Key Responsibilities

  • Apply statistical techniques and machine learning methods to solve complex business problems.
  • Build, validate, and deploy predictive and analytical models using Python.
  • Perform data extraction, transformation, and analysis using SQL across large datasets.
  • Work on causal inference techniques such as causal ML, matching models, or uplift modeling to evaluate business interventions.
  • Collaborate with product, business, and engineering teams to translate requirements into scalable data solutions.
  • Present insights, findings, and recommendations clearly to technical and non-technical stakeholders.
  • Ensure data quality, model performance, and continuous improvement of analytical workflows.

Requirements

  • 8 years of experience in data science and ML models
  • Hands-on expertise in Python and SQL for data analysis and modelling.
  • In-depth experience with A/B testing or similar methodologies such as Causal ML, Matching Models, or Auto ML.
  • Strong problem-solving skills with the ability to work independently on end-to-end data science projects.
  • Excellent communication skills and stakeholder management experience.
  • Solid understanding of regression, classification, and statistical methods

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.