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Remote Data Scientist Machine Learning Jobs in Wisconsin

Develop and implement statistical and machine learning models * Fine-tune, optimize and ensure the ... Translate data science outputs into business outcomes and value delivered * Mentor and guide junior ...

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Scientist I

Madison, WI · On-site +1

$60K - $80K/yr

This position is in-person and eligible for a partially remote schedule. Key Job Responsibilities ... Training and/or published research in data science & machine learning * Domain expertise in high ...

$225K - $260K/yr

This includes ensuring data is efficiently loaded, distributed, and processed across large GPU ... Work closely with ML scientists and other engineers to integrate new models, experiments, and ...

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

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Remote Data Scientist Machine Learning information

What does a Remote Data Scientist specializing in Machine Learning do?

A Remote Data Scientist specializing in Machine Learning uses advanced statistical techniques and programming skills to analyze large datasets and build predictive models, all while working from a remote location. They design, develop, and deploy machine learning algorithms to solve business problems, such as forecasting trends or automating processes. Their work often involves data cleaning, feature engineering, model selection, and collaborating with cross-functional teams to integrate these models into products or services. Remote data scientists typically use tools like Python, R, and cloud-based platforms to perform their tasks efficiently.

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

AspectRemote Data Scientist Machine LearningRemote Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; experience with ML frameworksSimilar educational background; may focus more on statistical analysis and data visualization
Work EnvironmentPrimarily involves developing ML models, coding in Python/R, and deploying algorithmsFocuses on data analysis, reporting, and insights generation, often with less emphasis on ML deployment
Employer & Industry UsageUsed in tech, finance, healthcare for predictive modeling and automationCommon across various industries for data analysis and business intelligence

While both roles require strong analytical skills and similar educational backgrounds, Remote Data Scientist Machine Learning specializes in developing and deploying machine learning models, whereas Remote Data Scientist focuses more on data analysis and reporting. The ML role often involves coding and algorithm development, making it more technical in nature.

How do remote data scientists specializing in machine learning typically collaborate with cross-functional teams?

Remote data scientists in machine learning often work closely with product managers, engineers, and business analysts through virtual meetings, collaborative platforms, and shared documentation tools. They regularly participate in sprint planning, code reviews, and brainstorming sessions to ensure alignment with project goals. Effective communication and proactive updates are essential for overcoming the challenges of remote collaboration and maintaining project momentum. Building strong relationships with team members across different time zones helps foster innovation and ensures that machine learning solutions are well-integrated into broader business objectives.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist specializing in Machine Learning, and why are they important?

To excel as a Remote Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, scikit-learn, PyTorch, and experience with cloud platforms like AWS or Azure are often required, along with relevant certifications. Strong problem-solving skills, effective communication, and the ability to work independently are crucial soft skills for remote collaboration and translating insights for diverse stakeholders. These competencies ensure the development of robust models, clear communication of findings, and successful project delivery in a distributed work environment.
What are the most commonly searched types of Data Scientist Machine Learning jobs in Wisconsin? The most popular types of Data Scientist Machine Learning jobs in Wisconsin are:
What are popular job titles related to Remote Data Scientist Machine Learning jobs in Wisconsin? For Remote Data Scientist Machine Learning jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Remote Data Scientist Machine Learning jobs in Wisconsin look for? The top searched job categories for Remote Data Scientist Machine Learning jobs in Wisconsin are:
What cities in Wisconsin are hiring for Remote Data Scientist Machine Learning jobs? Cities in Wisconsin with the most Remote Data Scientist Machine Learning job openings:
Data Scientist II (Remote)

Data Scientist II (Remote)

KOHLS

Menomonee Falls, WI • On-site, Remote

Other

Posted 14 days ago


Kohl's rating

5.8

Company rating: 5.8 out of 10

Based on 1,438 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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