ZipRecruiter

Log In

1

Data Scientist Machine Learning Jobs (NOW HIRING)

Nelo Mobile

Data Scientist (Machine Learning)

New York, NY · On-site

$180K - $230K/yr

Move fast, learn fast: hundreds of experiments run monthly; rigorous experimentation culture Why this Role is Different Most Data Science roles currently on the market are focused on optimizing ad ...

SOLTECH

Data Scientist

Duluth, GA · On-site

Senior Data Scientist (Machine Learning & MLOps) Our client is seeking a Data Scientist (Machine Learning & MLOps) to help build the next generation of its intelligent water utility platform. This is ...

Parsons

Machine Learning / Data Scientist

Washington, DC · On-site

$88K - $154K/yr

We have a career opportunity for a Machine Learning / Data Scientist to develop advanced analytical models and experiments that enhance decision-making, improve forecasting, and uncover insights ...

PTR Global

Sr Data Scientist

Fort Worth, TX · On-site

$90 - $100/hr

Data Scientist - Machine Learning & Generative AI Location: Fort Worth, TX 76155 (Hybrid) Durations: 6-12+ Months with possible extension and conversions. Job Overview: We are seeking a Data ...

previous pagenext page

Showing results 21-40

All JobsData Scientist Machine Learning Jobs

DATA Scientist Machine Learning information

See salary details

$37.5K

$122.7K

$196.5K

How much do data scientist machine learning jobs pay per year?

As of Aug 6, 2026, the average yearly pay for data scientist machine learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a data scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

More about DATA Scientist Machine Learning jobs
What cities are hiring for Data Scientist Machine Learning jobs? Cities with the most Data Scientist Machine Learning job openings:
What are the most commonly searched types of Data Scientist Machine Learning jobs? The most popular types of Data Scientist Machine Learning jobs are:
What states have the most Data Scientist Machine Learning jobs? States with the most job openings for Data Scientist Machine Learning jobs include:
What job categories do people searching Data Scientist Machine Learning jobs look for? The top searched job categories for Data Scientist Machine Learning jobs are:
DATA Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Sr. Principal Data Scientist / Machine Learning Engineer

Ascentt

Plano, TX • On-site

Full-time

Re-posted 2 days ago

Job description

Job Summary:
Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We are seeking a skilled Sr. Principal Data Scientist / Machine Learning Engineer to lead high-impact AI/ML projects, leveraging deep data science expertise to drive business value and client satisfaction.
Responsibilities:
• Serve as a primary technical expert and thought leader in Data Science and Machine Learning.
• Define and drive the technical strategy for AI/ML initiatives, identifying high-value opportunities for optimization, predictive analytics, and process improvement across diverse use cases.
• Architect and oversee the development of robust, scalable, and production-ready DS/ML models and solutions.
• Stay at the forefront of the latest advancements in DS/ML, especially those applicable to various industries and large-scale data problems.
• Lead end-to-end DS/ML projects, including requirements gathering, data exploration, model development, validation, deployment, and monitoring.
• Define project scope, timelines, and deliverables, ensuring successful execution within budget and schedule constraints.
• Mentor and guide junior and mid-level data scientists and ML engineers, fostering a culture of technical excellence and continuous learning.
• Drive MLOps best practices for reliable and efficient model deployment and lifecycle management.
• Act as a trusted advisor to clients and internal stakeholders, understanding their business challenges and translating them into solvable DS/ML problems.
• Effectively communicate complex analytical findings, model performance, and business recommendations to both technical and non-technical audiences.
• Manage client expectations, present progress reports, and ensure stakeholder satisfaction.
• Facilitate workshops and discovery sessions to identify new opportunities for AI/ML adoption.
• Lead the identification, prioritization, and execution of complex AI/ML use cases that drive significant business impact.
• Apply deep analytical skills to dissect complex problems, derive actionable insights from data, and design innovative solutions.
• Develop and implement models for:
• Predictive Analytics: Forecasting, risk assessment, and anomaly detection.
• Optimization: Improving efficiency, resource allocation, and decision-making.
• Pattern Recognition: Identifying trends, segments, and relationships within large datasets.
• Automation: Leveraging ML for intelligent process automation and enhanced operational efficiency.
Qualifications:
Required:
• Master's or Ph.D. in Data Science, Machine Learning, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.
• 8+ years of progressive experience in Data Science and Machine Learning roles, with at least 3-5 years in a leadership or principal-level capacity.
• Demonstrated experience leading multiple end-to-end DS/ML projects successfully from concept to production.
• Proven track record of managing client interactions, presenting technical solutions, and influencing strategic decisions.
• Expertise in Python programming (NumPy, Pandas, Scikit-learn, Keras/TensorFlow/PyTorch).
• Strong understanding of statistical modeling, experimental design, and hypothesis testing.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps principles.
• Excellent communication, interpersonal, and presentation skills.
Preferred:
• Experience with real-time data processing and streaming analytics.
• Knowledge of various industry verticals and their unique data challenges (e.g., finance, healthcare, retail, logistics, manufacturing).
• Experience with large-scale data architectures (e.g., data lakes, data warehouses, distributed computing).
• Publications or presentations in relevant fields.
Company:
Ascentt is an AI, ML and Data Science solutions provider serving enterprise customers. Founded in 2007, the company is headquartered in Plano, USA, with a team of 201-500 employees. The company is currently Growth Stage.

Apply