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Temporary Machine Learning Scientist Jobs in Indiana

Relativity

Principal Applied Scientist

Indianapolis, IN · On-site

Applied Science Team The Applied Science team sits at the core of Relativity's AI development. We ... Select the appropriate modeling approach for each problem, ranging from classical machine learning ...

Simos

Machine Technical Associate

Greenfield, IN · On-site

$22 - $30/hr

This Temp-to-Hire opportunity pays $22-$30 an hour. Ready to dive into the world of machine learning? Perks & Benefits * Weekly paychecks * Direct Deposit or Cash Card pay options * Medical / Dental ...

Elanco

Senior Data Scientist

Indianapolis, IN

Senior Data Scientist We are seeking a highly motivated and experienced Senior Data Scientist to ... Apply advanced modeling techniques, including machine learning, deep learning, statistical methods ...

Elanco

Senior Data Scientist

Indianapolis, IN · On-site

Senior Data Scientist We are seeking a highly motivated and experienced Senior Data Scientist to ... Apply advanced modeling techniques, including machine learning, deep learning, statistical methods ...

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Temporary Machine Learning Scientist information

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

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What are Temporary Machine Learning Scientists?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do Temporary Machine Learning Scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

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

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.
What are the most commonly searched types of Machine Learning Scientist jobs in Indiana? The most popular types of Machine Learning Scientist jobs in Indiana are:
What are popular job titles related to Temporary Machine Learning Scientist jobs in Indiana? For Temporary Machine Learning Scientist jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Scientist jobs in Indiana look for? The top searched job categories for Temporary Machine Learning Scientist jobs in Indiana are:
What cities in Indiana are hiring for Temporary Machine Learning Scientist jobs? Cities in Indiana with the most Temporary Machine Learning Scientist job openings:
Temporary Machine Learning Scientist jobs near you
Infographic showing various Temporary Machine Learning Scientist job openings in Indiana as of July 2026, with employment types broken down into 17% Internship, and 83% Full Time. Highlights an 68% In-person, and 32% Remote job distribution.

Research Scientist

Indiana University Academic Positions

Bloomington, IN • On-site

$70/hr

Other

Re-posted 25 days ago

Job description

Position Details
Title Research Scientist Appointment Status Non-Tenure Track Department IU Bloomington Psychological & Brain Sciences Location Bloomington Position Summary
Research Scientist for Indiana University Cognitive Development Lab

The Cognitive Development Lab at Indiana University-Bloomington (PI: Linda Smith) invites applications for a Research Scientist to assist in the creation and analysis of a shareable data set (of already collected data) from nearly 10,000 children ages 15 to 36 months. There is both a scientific premise and a methodological premise underlying the project.
The scientific premise is that developmental changes in visual cognition and early vocabulary development interact, with advances in visual cognition supporting early language learning and also being changed by language learning. The literature indicates multiple causal factors and inflection points that can disrupt this early stage of vocabulary growth- limitations in audition, or vision, in phonological representations, in visual attention, in the composition of early vocabularies, and in the quality and composition of language input.
The methodological premise concerns how to leverage all the data that has been already collected on these issues; experiments with many of the same overlapping measures designed with specific hypotheses in mind. The methodological premise for this project is that given some overlapping measures in the individual data sets and through the use of advanced analytic tools including machine learning and graph theoretics, one can discover multiple developmental pathways in cross-sectional data and the factors that underlie the trajectories of those pathways. These inferred pathways then can be empirically tested in longitudinal studies.
Strong applicants will have quantitative and computational training as well as experience in behavioral science, ideally in development, language, or visual cognition.
The successful applicant will have:
Excellent research track record.
Excellent programming skills.
Experience in computational and statistical methods and analyses including either graph theoretic of machine learning approaches (or both).
A track record of initiative, ability to lead a team (of undergraduates/masters students) and effective teamwork.
Fit of this project with their own career trajectory/goals
PhD in Psychology or related field


How to Apply: Interested candidates should apply at
https://indiana.peopleadmin.com/postings/26344 by submitting a cover letter describing your interests and prior experiences, CV, and contact information for three references. Applications will be accepted on an ongoing basis until the position is filled. Application review will start December 1, 2024. Anticipated start date is February 1, 2025. Start date is negotiable.

Questions regarding the position or application process can be directed to: Dr. Linda Smith (smith4@iu.edu).
Basic Qualifications
Excellent research track record.
Excellent programming skills.
Experience in computational and statistical methods and analyses including either graph theoretic of machine learning approaches (or both).
A track record of initiative, ability to lead a team (of undergraduates/masters students) and effective teamwork.
Fit of this project with their own career trajectory/goals
PhD in Psychology or related field
Department Contact for Questions
Dr. Linda Smith (smith4@iu.edu)
Additional Qualifications Salary and Rank $70-75,000, RS3 Special Instructions For Best Consideration Date 12/01/2024 Expected Start Date 02/01/2025 Posting Number IU-101078-2024

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