1

On Call Machine Learning R Jobs in Austin, TX (NOW HIRING)

... machine learning to help optimize marketing channels, via observational testing frameworks ... R, SQL, Java, or C++ Experience with cloud platforms, Spark, Docker, and MLOps tools and best ...

... machine learning to help optimize marketing channels, via observational testing frameworks ... R, SQL, Java, or C++ Experience with cloud platforms, Spark, Docker, and MLOps tools and best ...

The candidate will use machine learning, artificial intelligence, statistical modeling, data mining ... Analytical skills with a solid foundation in programming (R, SAS, Python, SQL, NoSQL, PostgreSQL ...

The candidate will use machine learning, artificial intelligence, statistical modeling, data mining ... Analytical skills with a solid foundation in programming (R, SAS, Python, SQL, NoSQL, PostgreSQL ...

Strong programming skills in Python, R, SQL, or similar tools. * Hands-on experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. * Experience developing predictive ...

Solid programming and data analysis skills in Python and/or R * Exposure to machine learning, statistical modelling, or optimisation techniques is a plus * Bachelor's degree in a technical discipline ...

Responsible for developing and improving low-power flow algorithms using AI and machine learning ... route (P&R). You'll actively leverage various AI tools to innovate new solutions and enhance ...

You'll be a hands-on technical leader, designing and deploying machine learning models in ... Advanced proficiency with SQL in big data environments, Python/R for large-scale analysis, and ...

... R, Java) for modeling or automation; architecting core BI reporting infrastructure (e.g., SQL development for internal tools, dashboard creation); or engineering/fine-tuning core machine learning ...

Apply Early

... R, Java) for modeling or automation; architecting core BI reporting infrastructure (e.g., SQL development for internal tools, dashboard creation); or engineering/fine-tuning core machine learning ...

... R, Java) for modeling or automation; architecting core BI reporting infrastructure (e.g., SQL development for internal tools, dashboard creation); or engineering/fine-tuning core machine learning ...

... R, Java) for modeling or automation; architecting core BI reporting infrastructure (e.g., SQL development for internal tools, dashboard creation); or engineering/fine-tuning core machine learning ...

Apply Early

next page

Showing results 1-20

On Call Machine Learning R information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

How much do on call machine learning r jobs pay per year?

As of Jul 1, 2026, the average yearly pay for on call machine learning r in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

Can you use R for machine learning?

Yes, machine learning R is widely used for data analysis, statistical modeling, and building predictive algorithms. R offers numerous packages like caret, randomForest, and xgboost that facilitate machine learning tasks, making it a popular choice among data scientists and analysts. Proficiency in R can be valuable for roles involving data-driven decision making and model deployment.

What is the difference between On Call Machine Learning R vs Data Scientist?

AspectOn Call Machine Learning RData Scientist
Required CredentialsTypically requires proficiency in R, statistical analysis, and some machine learning knowledgeRequires advanced degrees (often Master’s or PhD), programming skills (R, Python), and data analysis expertise
Work EnvironmentOften on-demand, project-based, or support roles within organizations or consulting firmsFull-time roles in various industries, involving data analysis, model development, and strategic insights
Employer & Industry UsageUsed by companies needing immediate machine learning support or troubleshootingEmployed across industries for data-driven decision making and predictive modeling

While both roles involve machine learning and R, On Call Machine Learning R focuses on providing immediate, project-specific support using R, whereas Data Scientists typically work on comprehensive data analysis and model development in a full-time capacity.

Is ML a high paying job?

Machine Learning (ML) roles are generally considered high-paying within the tech industry due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and company, but ML positions often offer competitive compensation compared to other data-related roles.

Which 5 jobs will survive AI?

For an On Call Machine Learning R, roles that involve complex problem-solving, creativity, and human interaction are more likely to persist, such as data scientists, AI ethics specialists, machine learning engineers, domain-specific consultants, and technical trainers. These jobs require advanced expertise, critical thinking, and adaptability that AI is less capable of replicating. Continuous learning and staying updated with new tools and techniques are essential for long-term job security in this field.

What jobs can you get with R?

With R skills, you can pursue roles such as data analyst, data scientist, statistical programmer, and machine learning engineer. These jobs typically involve data analysis, statistical modeling, and building predictive models, often requiring knowledge of data visualization and statistical packages in R.
Applied Scientist

$171K - $302K/yr

Full-time

Medical, Dental, Retirement

Posted 27 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 666 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps, award-winning shows and movies, immersive music in spatial audio, world-class workouts and meditations, super fun games and more! The Services Data Science & Analytics organization is passionate about developing discerning insights and AIML solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy.
We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help optimize marketing channels, via observational testing frameworks, counterfactual modeling, and lifetime value estimation. As a key member of our diverse organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to privacy that will frequently require novel approaches. You'll work alongside partners across Business, Marketing, Product, Finance, and Engineering daily to deliver material customer and business value.
Description
As an Applied Scientist, you will have the responsibility of pushing the boundaries of how Causal Inference and AIML can be leveraged to better serve our customers. You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference solutions, that directly impact our products and provide a granular understanding of key marketing effectiveness. You will also be instrumental in defining the technical vision, strategy, and execution roadmap for our AIML initiatives, ensuring that we deliver high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges. You will also be a key driver in fostering a vibrant culture of innovation, continuous learning, and collaborative problem-solving.","responsibilities":"Engineer end-to-end scalable and robust Causal Inference products which provide Apple with an understanding of the health of our Services’ marketing efforts.
Dive deep into large-scale data sources to uncover opportunities for Causal Inference automation, predictive methods, and quantitative modeling.
Collaborate with product managers, data scientists, and other engineering teams to translate business requirements into technical specifications and deliver impactful, practical solutions, increasing internal adoption of causal inference approaches and democratizing data
Stay abreast of the latest advancements in causal inference and AIML research, evaluating and integrating new frameworks where appropriate
Champion best practices in software engineering, MLOps, code quality, testing, documentation, and ensure compliance with data privacy and security
Preferred Qualifications
PhD in related field
Hands-on experience leveraging Generative AI to improve productivity and generate new insights
Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action
Minimum Qualifications
Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field
3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist role
Familiarity with a brand range of quasi-experimental Causal Inference techniques such as diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matching
Hands-on experience building Marketing Mix models and validation through Matched Market testing
Solid understanding of AIML technologies including Generative AI
Proven track record of successfully delivering complex projects from start to finish
Proficiency in programming languages such as Python, R, SQL, Java, or C++
Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices
Excellent communication, collaboration, and presentation skills with meticulous attention to detail
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 and $302,200, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976