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Remote Aws Machine Learning Jobs in Denton, TX (NOW HIRING)

Lead Research Engineer

Frisco, TX · On-site +1

$95K - $126K/yr

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

AWS/GCP acceptable) * Advanced SQL skills and experience with OLTP and OLAP data modeling * Solid ... Experience supporting machine learning workflows or analytical data science pipelines * Knowledge ...

Demonstrated expertise in building and deploying AI/Machine Learning solutions at scale leveraging cloud such as AWS, Azure, or Google Cloud Platform. * Experience in developing and maintaining APIs ...

Demonstrated expertise in building and deploying AI/Machine Learning solutions at scale leveraging cloud such as AWS, Azure, or Google Cloud Platform. * Experience in developing and maintaining APIs ...

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

REMOTE Anticipated Start Date: 07/01/2026 The US base salary range for this full-time position is ... Lead the development and deployment of advanced machine learning models to forecast outcomes and ...

... and remote work on Fridays Who we're looking for: Toyota Financial Services is seeking highly ... Hands-on experience with cloud-based machine learning platforms (e.g., AWS SageMaker or Azure ML ...

Remote Duration: Long term contract We are seeking a highly skilled Full Stack Developer with over ... Deploy, scale, and monitor machine learning workloads on AWS (SageMaker, Lambda, or ECS)

Showing results 21-40

Remote Aws Machine Learning information

What are the key skills and qualifications needed to thrive as a remote AWS Machine Learning engineer?

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What is a remote AWS Machine Learning job?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

What is the difference between Remote Aws Machine Learning vs Remote Data Scientist?

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.
What are popular job titles related to Remote Aws Machine Learning jobs in Denton, TX? For Remote Aws Machine Learning jobs in Denton, TX, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in Denton, TX look for? The top searched job categories for Remote Aws Machine Learning jobs in Denton, TX are:
What cities near Denton, TX are hiring for Remote Aws Machine Learning jobs? Cities near Denton, TX with the most Remote Aws Machine Learning job openings:

WFP Lead Data Scientist - Vice President

JP Morgan Chase

Plano, TX • On-site, Remote

Full-time

Medical, Retirement

Re-posted 11 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

72nd of 171 rated banks


Job description

The Workforce Planning (WFP) organization is a part of Consumer and Community (CCB) Operations division. The WFP Data Science organization is tasked with delivering quantitatively driven solutions to support the core WFP functions (demand forecasting, capacity planning, resource scheduling, and business analysis & support). The WFP organization supports Chase's call centers, back office, and ~5,200 retail branches.

As a Data Scientist Lead - WFP Machine Learning Scientist, within JPMorganChase, you will engage in projects by the Artificial Intelligence(AI)/Machine Learning(ML) team that can be complex, data intensive, and of a high level of difficulty, each having significant impact on the business.  You will typically encounter these problems which will be of an unstructured nature, whereby the employee will be expected to quickly assess and comprehend the situation then develop a practical problem solving strategy.  You will be expected to analyze the topic in question, develop solution proposals and review their results and next steps with management for prioritization, timing, and delivery. The AI/ML team is tasked with building next-gen data science solutions that move us closer to real-time inference and decision making.

Job Responsibilities

  • Design and development of Machine Learning, Artificial Intelligence and Statistical models.
  • Participate in the full model development lifecycle, from framing the problem to prepare documentation and passing independent model review (MRGR).
  • Lead AI/ML projects along with mentor and coach junior team members.
  • Collaborate with stakeholders to understand the business requirements and clearly define the objectives of any solution.
  • Identify and select the correct method to solve the problem while staying up to data on the latest AI/ML research
  • Ensure the robustness of any data science solution.
  • Develop and communicate recommendations and data science solutions in easy-to-understand-way leveraging data to tell a story.
  • Lead and persuade others while positively influencing the outcome of team efforts and help frame a business problem into a technical problem resulting in a feasible solution.

Required Qualifications, Capabilities, and Skills

  • Master's Degree with 5+ years or Doctorate (PhD) with 3+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines.
  • 2+ years of experience leading AI/ML projects with multiple team members
  • Hands-on experience developing statistical models, machine learning models, and/or artificial intelligence models.
  • Deep understanding of math and theory behind AI/ML algorithms.
  • Proficient in data science programming languages like Python, R or Scala.
  • Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
  • Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence. 

Preferred Qualifications, Capabilities, and Skills

  • Advanced expertise with Time Series and Operations Research techniques. 
  • Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills.
  • Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
  • Previous experience leading highly complex cross-functional technical projects with multiple stakeholders

This position is full time in office Monday - Friday.  This position is not hybrid nor remote.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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