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Weekend No Experience Machine Learning Jobs in Oregon

OR · On-site

The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in ...

OR · On-site

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. A few examples: * We build state-of-the-art models powering Search, Discovery, and ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... No commuting required. * Get matched with students best-suited to your teaching style and expertise.

Machine Learning Tutor

OR · Remote

$40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... No commuting required. * Get matched with students best-suited to your teaching style and expertise.

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... No commuting required. * Get matched with students best-suited to your teaching style and expertise.

OR · On-site

$114.40K - $137.40K/yr

The ideal candidate will have hands-on experience with Google Cloud Document AI, Vertex AI, and ... Design, develop, train, and fine-tune machine learning models, including custom and pre-trained ...

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Weekend No Experience Machine Learning information

What are the key skills and qualifications needed to thrive as a Machine Learning professional with no prior experience working weekends, and why are they important?

To thrive as a Machine Learning professional, foundational knowledge in mathematics, statistics, and programming (especially Python) is essential, typically demonstrated through coursework or self-directed learning. Familiarity with machine learning libraries such as scikit-learn or TensorFlow and version control systems like Git is highly beneficial, even at an entry level. Curiosity, problem-solving abilities, and effective communication help newcomers stand out as they learn quickly and collaborate with more experienced team members. These skills and qualities are crucial to building practical expertise, contributing to projects, and adapting to the evolving demands of machine learning roles.

What kind of support and training can I expect as someone starting a weekend machine learning role with no prior experience?

In a weekend machine learning role designed for beginners, you can typically expect onboarding sessions, access to online learning materials, and mentorship from more experienced team members. Many organizations provide structured guidance through tutorials, code reviews, and collaborative projects to help you build foundational skills. You’ll likely be assigned manageable tasks that allow you to gradually familiarize yourself with real datasets and tools, while regular feedback ensures your steady progress. Team meetings and open communication channels are common, so don’t hesitate to ask questions and seek help as you learn.

What is a Weekend No Experience Machine Learning job?

A Weekend No Experience Machine Learning job is a part-time opportunity typically scheduled on weekends for individuals interested in machine learning but who have little or no prior experience in the field. These jobs are designed for beginners and may involve tasks such as data labeling, assisting with simple coding projects, or supporting research teams. They provide a great entry point for those looking to gain hands-on experience, learn industry tools, and build their resumes while balancing other commitments like school or a full-time job.

What is the difference between Weekend No Experience Machine Learning vs Weekend Data Analyst?

AspectWeekend No Experience Machine LearningWeekend Data Analyst
Required CredentialsBasic understanding of programming, no formal certification neededBasic knowledge of data analysis tools, possibly some certifications
Work EnvironmentProject-based, flexible hours, often remotePart-time, flexible hours, often remote or on-site
Industry UsageTech, finance, healthcare, startupsBusiness, marketing, finance, consulting

Weekend No Experience Machine Learning roles focus on introductory tasks like data preprocessing and basic model training, suitable for beginners. Weekend Data Analyst positions involve analyzing datasets, creating reports, and supporting decision-making. Both roles are flexible and often part-time, but they differ in technical depth and industry focus.

What are popular job titles related to Weekend No Experience Machine Learning jobs in Oregon? For Weekend No Experience Machine Learning jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Weekend No Experience Machine Learning jobs in Oregon look for? The top searched job categories for Weekend No Experience Machine Learning jobs in Oregon are:
What cities in Oregon are hiring for Weekend No Experience Machine Learning jobs? Cities in Oregon with the most Weekend No Experience Machine Learning job openings:
Machine Learning PhD Intern, Economics

Machine Learning PhD Intern, Economics

Instacart

On-site

Other

Posted 9 days ago


Instacart rating

6.7

Company rating: 6.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

Overview

We are looking for interns to join Instacart's Economics team. The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in economics or related fields like marketing, finance, or operations research. Candidates should bring some relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications.

The Economics team at Instacart works on a range of interesting and challenging problems at the intersection of machine learning and economics, from aligning the incentives in our multi-sided marketplace to analyzing the impact of behavioral nudges on our customers' and shoppers' decisions. Some of the core areas of focus for our team include online advertising, uplift and long term value modeling, logistics, marketplace optimization (consumers, shoppers, retailers), inventory intelligence, and general causal inference. You can find more information in our blog post that introduces the team and the type of work we do.

About the Job

  • You will help design and build end-to-end machine learning solutions.
  • You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects.
  • You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains.
  • You will develop high impact solutions to support Instacart's ambitious growth plans.
  • You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments.
  • You will have the freedom to suggest and drive organization-wide initiatives.

About You

Minimum Qualifications

  • Current or recently graduated PhD student in economics or a related field with focus on data-intense problems.
  • A blend of economic theory, applied econometrics, and business acumen that let you jump into a fast-paced environment and contribute from day one.
  • Expertise in causal inference with observational and experimental data.
  • Expertise in Python or R and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
  • Self-motivation and a strong sense of ownership

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012