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Remote Aws Machine Learning Jobs in Wisconsin (NOW HIRING)

KOHLS

Data Scientist II (Remote)

Menomonee Falls, WI · On-site +1

Develop and implement statistical and machine learning models * Fine-tune, optimize and ensure the scalability of models and algorithms * Aid in designing experiments to answer targeted questions

CSAA

... AI and machine learning, and owning the key performance indicators tied to their initiatives ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

CSAA

... AI and machine learning, and owning the key performance indicators tied to their initiatives ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

CSAA

... AI and machine learning, and owning the key performance indicators tied to their initiatives ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

Relativity

Principal Applied Scientist

Milwaukee, WI · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Select the appropriate modeling approach for each problem, ranging from classical machine learning ...

Qualysoft

... Betrieb skalierbarer Machine-Learning- und LLM-Losungen auf Azure Databricks von der ... Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ...

State of Wisconsin

Data Engineer

Madison, WI · On-site +1

$82K - $102K/yr

... machine learning. The incumbent will serve as a subject matter expert as it relates to the Circuit ... Certain positions with this Department may allow remote work for a portion of their work schedule ...

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Remote Aws Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote AWS Machine Learning Engineer, and why are they important?

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 are remote AWS Machine Learning jobs?

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 the most commonly searched types of Aws Machine Learning jobs in Wisconsin? The most popular types of Aws Machine Learning jobs in Wisconsin are:
What are popular job titles related to Remote Aws Machine Learning jobs in Wisconsin? For Remote Aws Machine Learning jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in Wisconsin look for? The top searched job categories for Remote Aws Machine Learning jobs in Wisconsin are:
What cities in Wisconsin are hiring for Remote Aws Machine Learning jobs? Cities in Wisconsin with the most Remote Aws Machine Learning job openings:
Remote Aws Machine Learning jobs near you
Data Scientist II (Remote)

Data Scientist II (Remote)

KOHLS

Menomonee Falls, WI • On-site, Remote

Other

Posted 2 days ago

Kohl's rating

5.8

Company rating: 5.8 out of 10

Based on 1,435 frontline employees who took The Breakroom Quiz

12th of 21 rated department stores

Job description

About the Role

In this role you will work with a data science team and cross-functional partners to solve business challenges and promote data-driven decision making with advanced data analysis and machine learning.

What You’ll Do

  • Lead exploratory data analysis to cull actionable insights

  • Collaborate with stakeholders to understand business requirements and translate them into technical solutions

  • Develop and implement statistical and machine learning models 

  • Fine-tune, optimize and ensure the scalability of models and algorithms

  • Aid in designing experiments to answer targeted questions

  • Identify and drive continuous improvement of key business metrics in an assigned business functional area

  • Drive adoption and usage of data science products and models

  • Translate data science outputs into business outcomes and value delivered

  • Mentor and guide junior data scientists, providing technical expertise and fostering a culture of continuous learning and development

  • Stay up to date on the latest trends and developments in data science and technology and identify implementation opportunities to support innovation at Kohl’s

  • Additional tasks may be assigned

Addendum

PERSONALIZATION & RECOMMENDATION SYSTEMS

Accountabilities

  • Design and support deployment of machine learning models to power personalized experiences across digital channels (e.g., homepage, PDP, cart, campaigns)

  • Build and optimize recommendation and ranking systems balancing relevance, discovery, and business objectives (e.g., conversion, revenue)

  • Develop multi-stage ranking approaches, including candidate generation and re-ranking

  • Address cold-start and long-tail challenges in large product catalogs

  • Partner with engineering to support real-time personalization and scalable deployment

Skills & Experience

  • Experience with recommendation systems, search, or ranking problems at scale of millions of customers and products

  • Experience in developing sequential, transformer models and utilizing LLM models in production

  • Understanding of collaborative filtering and learning-to-rank methods

  • Experience optimizing models for GPU / distributed training

  • Familiarity with large-scale datasets and production ML systems

  • Exposure to real-time or low-latency serving environments

  • Experience with vector search / ANN methods (e.g., FAISS, ScaNN) preferred

  • Experience with delivering end to end customized ML models in production environment

Required

  • Bachelor’s Degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field

  • 3+ years of progressively complex data science experience

  • Extensive experience developing and deploying state-of-the-art algorithms using machine learning, statistical and optimization methods 

  • Expert in using modern analytics tools, programming languages, and cloud platforms (Python, R, Spark, SQL, GCP, etc.)

  • Strong problem-solving skills with an emphasis on product development

  • Experience proposing rapid experiments to test the effectiveness of new strategies or initiatives and iterating quickly

  • Effective communication and collaboration skills at all levels 

Preferred

  • Master’s degree and/or Ph.D.

  • Retail and Logistics experience

  • Supply chain management

  • Marketing models

What Kohl's employees say

Pay

Benefits

Hours and flexibility

Workplace

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