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Remote Data Scientist Experimentation Jobs in Indiana

Circle

Staff Software Engineer, Data Platform

Miami, IN · On-site +1

... Science teams by enabling experimentation, operational excellence, and actionable insights to ... Excellent communication skills, with the ability to collaborate across multiple remote teams, share ...

Circle

Staff Software Engineer, Data Platform

Austin, IN · On-site +1

... Science teams by enabling experimentation, operational excellence, and actionable insights to ... Excellent communication skills, with the ability to collaborate across multiple remote teams, share ...

Circle

Staff Software Engineer, Data Platform

Boston, IN · On-site +1

... Science teams by enabling experimentation, operational excellence, and actionable insights to ... Excellent communication skills, with the ability to collaborate across multiple remote teams, share ...

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Remote Data Scientist Experimentation information

What does a remote data scientist experimentation do?

A Remote Data Scientist Experimentation specializes in designing, conducting, and analyzing experiments such as A/B tests to inform product or business decisions. They work remotely, using statistical methods and data analysis tools to test hypotheses, measure outcomes, and provide actionable insights. Their role often involves collaborating with product, engineering, and marketing teams to ensure experiments are well-designed and results are effectively communicated. By optimizing experimentation processes and interpreting complex data, they help organizations make data-driven decisions from anywhere.

What are the key skills and qualifications needed to thrive as a remote data scientist experimentation?

To thrive as a Remote Data Scientist specializing in Experimentation, you need strong proficiency in statistics, experimental design, data analysis, and a solid foundation in programming languages like Python or R, typically backed by a degree in a quantitative field. Familiarity with A/B testing platforms, data visualization tools, and cloud-based analytics systems is crucial, along with experience using SQL and machine learning libraries. Exceptional problem-solving abilities, attention to detail, and clear communication skills set top performers apart, especially when collaborating remotely. These skills ensure sound experimental methodology, actionable insights, and effective teamwork in a distributed work environment.

How does a remote data scientist experimentation typically collaborate with cross-functional teams to design and analyze experiments?

As a Remote Data Scientist specializing in experimentation, you'll frequently work with product managers, engineers, and UX researchers to identify business questions that can be addressed through A/B testing or other experimental designs. Collaboration often happens through virtual meetings, shared documentation, and project management tools. You'll be responsible for helping teams define hypotheses, select appropriate metrics, design experiments, analyze results, and communicate findings. Strong communication skills are essential, as you'll need to translate statistical insights into actionable recommendations for non-technical stakeholders.

What is the difference between Remote Data Scientist Experimentation vs Remote Data Scientist?

AspectRemote Data Scientist ExperimentationRemote Data Scientist
CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; experience with experimentation toolsBachelor's/Master's in Data Science, Statistics, or related fields; strong analytical skills
Work EnvironmentFocus on designing and analyzing experiments, A/B testing, and causal inferenceBroader data analysis, modeling, and predictive analytics
Industry UsageCommon in e-commerce, SaaS, and product teams emphasizing experimentationUsed across various industries for data analysis and modeling

Remote Data Scientist Experimentation specializes in designing and analyzing experiments like A/B tests to optimize products, while Remote Data Scientist has a broader role in data analysis, modeling, and predictive analytics. Both roles require similar educational backgrounds but differ in focus and application.

What are the most commonly searched types of Data Scientist Experimentation jobs in Indiana?

The most popular types of Data Scientist Experimentation jobs in Indiana are:

What are popular job titles related to Remote Data Scientist Experimentation jobs in Indiana?

For Remote Data Scientist Experimentation jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Remote Data Scientist Experimentation jobs in Indiana look for?

The top searched job categories for Remote Data Scientist Experimentation jobs in Indiana are:

What cities in Indiana are hiring for Remote Data Scientist Experimentation jobs?

Cities in Indiana with the most Remote Data Scientist Experimentation job openings:

Remote Data Scientist Experimentation jobs near you

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Carmel, IN • Remote

$80 - $110/hr

Part-time

Posted 19 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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