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Overnight Environmental Data Scientist Jobs in Indiana

Data Scientist

Warsaw, IN · On-site

$60 - $80/hr

As a mid-level Data Scientist at Samba in Warsaw, you will own end-to-end delivery of significant ... We celebrate diversity and are committed to creating an inclusive environment for all employees. We ...

... flexible environment that helps them succeed both at work and at home. Join our dynamic ... In this role, you'll collaborate closely with senior data scientists to build and support AI/ML and ...

... flexible environment that helps them succeed both at work and at home. Join our dynamic ... In this role, you'll collaborate closely with senior data scientists to build and support AI/ML and ...

... flexible environment that helps them succeed both at work and at home. Join our dynamic ... In this role, you'll collaborate closely with senior data scientists to build and support AI/ML and ...

... flexible environment that helps them succeed both at work and at home. Join our dynamic ... In this role, you'll collaborate closely with senior data scientists to build and support AI/ML and ...

... a Data Scientist to provide engineering and technical support to assist our government customer ... Develop and deploy AI/ML and computer Vision workflow tools within Linux environments to support ...

... environment with rich involvement in technology innovation, ERP and CRM counselling, Product ... Data Scientist Location: Columbus, IN Duration: 9 weeks Primary Skills: this is a fixed fee project ...

Data Scientist - JETARS

Fort Wayne, IN · On-site

$125 - $150/hr

We take pride in supporting our nation's most critical missions while creating an environment where ... Position Summary The Garrett Group is seeking an experienced Data Science and Analytics ...

Operatewithin Agile development environments while collaborating with cross-functional teams across ... Minimum of 7+ years of combined experience in data science, data visualization, artificial ...

Data Scientist Senior Data Scientist Senior Location: Ideal candidates will be able to report to ... Piping and processing massive data-streams in distributed computing environments such as Denodo to ...

Data Scientist Senior Data Scientist Senior Location: This role requires associates to be in-office ... environments such as Hadoop. * Recommends appropriate batch and real-time model scoring to drive ...

... environments. What You'll Do: * Design and implement adaptive process control strategies ... D. + 3 years' experience in Data Science, Computer Science, Chemical Engineering, Bioprocess ...

Data Scientist Senior Data Scientist Senior Location: Ideal candidates will be able to report to ... Piping and processing massive data-streams in distributed computing environments such as Denodo to ...

Data Scientist Senior Data Scientist Senior Location: This role requires associates to be in-office ... environments such as Hadoop. * Recommends appropriate batch and real-time model scoring to drive ...

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Overnight Environmental Data Scientist information

What does an overnight environmental data scientist do?

An Overnight Environmental Data Scientist is responsible for analyzing environmental data, such as air quality, water quality, and weather patterns, during overnight hours to ensure timely reporting and response. They use statistical methods, programming, and specialized software to process large datasets collected from sensors and other monitoring devices. Their work helps organizations and agencies make data-driven decisions about environmental policies, compliance, and emergency responses. Overnight shifts are often required to provide continuous data monitoring and immediate analysis in case of environmental incidents.

What are some unique challenges faced by overnight environmental data scientists, and how can they be managed?

Overnight Environmental Data Scientists often work outside typical business hours, which can pose challenges such as limited real-time collaboration with day-shift colleagues and adjusting to an atypical sleep schedule. Managing these challenges involves strong communication skills, effective handover processes, and utilizing collaboration tools to ensure continuity across shifts. Additionally, overnight roles may involve real-time monitoring of environmental data streams and responding quickly to anomalies, making it important to stay alert and maintain a proactive approach to data quality and reporting.

What are the key skills and qualifications needed to thrive as an overnight environmental data scientist, and why are they important?

To excel as an Overnight Environmental Data Scientist, you need strong analytical skills, proficiency in environmental science concepts, and a degree in a relevant field such as environmental science, data science, or statistics. Familiarity with programming languages like Python or R, GIS software, and experience with data visualization and analysis tools are typically required, along with certifications such as Certified Data Scientist or GIS Professional. Excellent problem-solving, attention to detail, and effective communication are crucial soft skills for interpreting complex data and collaborating with remote or cross-functional teams. These skills are essential for accurately monitoring environmental trends, supporting real-time decision-making, and ensuring data-driven insights are delivered efficiently—especially during overnight shifts when independent work is critical.

What is the difference between Overnight Environmental Data Scientist vs Environmental Data Analyst?

AspectOvernight Environmental Data ScientistEnvironmental Data Analyst
CredentialsBachelor's or Master's in Environmental Science, Data Science, or related fields; proficiency in programming and statistical toolsBachelor's or Master's in Environmental Science, Data Analysis, or related fields; strong analytical skills
Work EnvironmentTypically in research labs, field sites, or data centers, often during overnight shiftsOffice settings, fieldwork, or remote analysis during regular hours
Employer & Industry UsageEnvironmental agencies, research institutions, and consulting firmsGovernment agencies, environmental consultancies, and private firms

The main difference is that Overnight Environmental Data Scientists focus on advanced data modeling and analysis during overnight shifts, often requiring programming skills and scientific expertise. Environmental Data Analysts typically handle data interpretation during regular hours, focusing on reporting and basic analysis. Both roles are vital in environmental sectors but differ mainly in scope, work hours, and technical depth.

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

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

What are popular job titles related to Overnight Environmental Data Scientist jobs in Indiana?

For Overnight Environmental Data Scientist jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Overnight Environmental Data Scientist jobs in Indiana look for?

The top searched job categories for Overnight Environmental Data Scientist jobs in Indiana are:

What cities in Indiana are hiring for Overnight Environmental Data Scientist jobs?

Cities in Indiana with the most Overnight Environmental Data Scientist job openings:

Data Scientist

Samba

Warsaw, IN • On-site

$60 - $80/hr

Other

Re-posted 9 days ago


Key responsibilities

  • Own end-to-end delivery of significant data science projects, including problem scoping, approach design, and production deployment.

  • Build and maintain production-quality Python and PySpark code, implementing advanced ML and AI workflows such as entity resolution, probabilistic record linkage, and semantic similarity.

  • Collaborate with cross-functional teams to translate business requirements into technical solutions and mentor junior data scientists on technical execution and best practices.


Job description

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant.

As a mid-level Data Scientist at Samba in Warsaw, you will own end-to-end delivery of significant data science projects with minimal guidance. You are a reliable, autonomous contributor with deep expertise in at least one of Samba's core domains — measurement, or audience modelling — and the technical range to build production-ready solutions using modern ML and AI methodologies. You'll work closely with peers, product, and engineering, and play an active role in mentoring junior data scientists on the team.

What You'll Do:
  • Own end-to-end delivery of significant data science projects — from problem scoping and approach design through to production deployment
  • Make sound, independently-reasoned decisions on methodology, model selection, and evaluation; document them clearly in technical solution documents covering problem statement, approach, metrics, and timeline
  • Lead solution design for your own initiatives; break down complex epics into well-scoped user stories with clear acceptance criteria, adopting DataOps and MLOps best practices throughout — experiment tracking, pipeline orchestration, model monitoring, and reproducibility
  • Build production-quality Python and PySpark code on Databricks — well-tested, documented, and reusable — and implement advanced ML and AI-powered workflows including entity resolution, probabilistic record linkage, embedding-based matching, semantic similarity, and LLM-augmented pipelines
  • Develop and maintain reusable tools, libraries, and documentation that improve team efficiency and technical standards; conduct code reviews with constructive, specific feedback that raises the bar
  • Mentor junior data scientists on technical execution, code quality, and career development; lead internal talks or workshops on ML topics
  • Collaborate cross-functionally with product, engineering, and operations — translate business requirements into technical specifications, partner with data engineering on scalable pipeline design, and participate in cross-functional design reviews and working groups
Who You Are:
  • Bachelor's degree required in Statistics, Data Science, Computer Science, Mathematics or a related quantitative field; Master's strongly preferred
  • 3–5 years of hands‑on data science experience with demonstrated ability to own and deliver complex, multi-sprint projects independently
  • Advanced Python with production-quality code, testing, and documentation; strong SQL and PySpark for billion-row datasets
  • Databricks workflows, Delta Lake, and job orchestration; working knowledge of cloud platforms (AWS or GCP)
  • Solid command of core ML — regression, classification, clustering, model evaluation, and experimental design — applied to complex, high-volume data
  • Proficiency with MLOps practices: experiment tracking, pipeline orchestration (Airflow), and reproducible model deployment
  • Exposure to modern AI methodologies: RAG systems, LLM-augmented models, vector databases, and semantic search
  • Strong communicator — able to translate technical work into clear documentation, user stories, and cross-functional conversations
  • Demonstrated ability to mentor junior data scientists and contribute to team standards
Preferred skills:
  • Hands-on experience with knowledge graph construction, entity resolution, or semantic data modeling (RDF, OWL, SPARQL, or equivalent graph frameworks)
  • Familiarity with probabilistic record linkage, identity graph approaches, or embedding-based entity matching at scale
  • Experience with causal inference methods (A/B testing, synthetic control, uplift modeling)
  • Experience with deduplication, enrichment, or web-to-TV linkage problems
  • Background in media, ad tech, or measurement — TV viewership (ACR/STB data), digital audience modeling, cross-platform measurement (linear + CTV/OTT), or identity resolution in privacy-constrained environments
  • Familiarity with the measurement and identity vendor landscape (Nielsen, Comscore, LiveRamp, The Trade Desk)

180,000 zł - 330,000 zł a year

Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.

Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU, Samba Inc. is the data controller.

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