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Remote Machine Learning Jobs in Crown Point, IN (NOW HIRING)

1 point system

Senior Data Scientist

Chicago, IL · Remote

... Remote Type of Hire 4 months contract They strictly want candidates from Insurance/ Claim with risk management background. The Sr Data Scientist will design and implement machine learning and NLP ...

Tempus

Manager, Regulatory Submissions (Remote)

Chicago, IL · On-site +1

$110K - $150K/yr

Machine learning validation requirements * Lifecycle management of medical devices/IVDs * Changes ... remote $110,000-$150,000 The expected salary range above is applicable if the role is performed ...

Kemper

Data Scientist

Chicago, IL · On-site +1

Solid understanding of statistical modeling and machine learning concepts, including model training ... Remote options are available for non-local candidate. * The range for this position is $93,300 to ...

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Remote Machine Learning information

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$24.2K

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$83.5K

How much do remote machine learning jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote machine learning in Crown Point, IN is $40,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,800.00 and $43,600.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
More about Remote Machine Learning jobs
What are popular job titles related to Remote Machine Learning jobs in Crown Point, IN? For Remote Machine Learning jobs in Crown Point, IN, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Crown Point, IN look for? The top searched job categories for Remote Machine Learning jobs in Crown Point, IN are:
What cities near Crown Point, IN are hiring for Remote Machine Learning jobs? Cities near Crown Point, IN with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Crown Point, IN as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $40,405 per year, or $19.4 per hour.

Senior Data Scientist

1 point system

Chicago, IL • Remote

Contractor

Re-posted 28 days ago

Job description

Complete JD:

Job Title

Senior Data Scientist

Location

Remote

Type of Hire

4 months contract

  

They strictly want candidates from Insurance/ Claim with risk management background.

The Sr Data Scientist will design and implement machine learning and NLP solutions for a claims and incident mitigation analytics project. This role will help risk management teams identify high-risk incidents earlier, classify claims by likely severity and financial impact, and provide explainable insights that support faster intervention. The position responsibilities outlined below are not all encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.

 

POSITION RESPONSIBILITIES:
• Translate risk management business requirements into well-defined data science solutions, including incident prioritization and claim severity classification.
• Profile, clean, and prepare claims and incident data for analytics, modeling, and scoring.
• Develop feature engineering logic using structured and unstructured claims and incident data.
• Apply NLP and text-processing techniques to claim and incident narratives to extract useful risk signals.
• Develop record-linkage approaches to connect incidents and claims when a clean unique identifier is not available.
• Build and validate models that rank incidents by likelihood of becoming claims or requiring Risk Management intervention.
• Build and validate claim severity models that classify claims by likely financial impact and high-dollar claim risk.
• Generate explainability outputs, including key risk drivers and business-readable reasons for flagged incidents or claims.
• Collaborate with Risk Management, Legal, Data Engineering, BI, Data Governance, and MLOps partners to deliver usable business outputs.
• Monitor model performance, drift, scoring quality, and retraining needs.
• Document modeling assumptions, feature logic, validation results, limitations, and handoff requirements.
• Ensure data science work follows data governance expectations, including appropriate handling of PII and sensitive fields.
• Present findings, model results, and recommendations to business and technical stakeholders in a clear, actionable manner.

 

EXPERIENCE AND QUALIFICATIONS:

 

Required Skills -
• Strong experience building supervised machine learning models, especially classification, ranking, and severity / risk scoring models.
• Strong experience with data profiling, data cleaning, feature engineering, model validation, and model evaluation.
• Experience working with messy, sparse, real-world enterprise datasets.
• Strong Python and SQL skills.
• Experience with NLP or text analytics, including narrative cleaning, text classification, embeddings, keyword extraction, or summarization.
• Experience with probabilistic record linkage, entity resolution, fuzzy matching, or deduplication.
• Experience explaining model outputs using feature importance, SHAP, reason codes, or other explainability methods.
• Experience working with Snowflake or similar enterprise data warehouse platforms.
• Experience supporting batch scoring, model monitoring, and production handoff.
• Strong understanding of data governance, sensitive data handling, and PII masking or exclusion.
• Excellent communication and teamwork skills.

PREFERRED SKILLS:
• Experience with insurance claims, risk management analytics, litigation analytics, fraud detection, or safety analytics.
• Experience with claim severity modeling or high-dollar claim prediction.
• Experience with AWS, SageMaker, or similar cloud-based data science environments.
• Experience supporting BI outputs in Tableau, Power BI, Looker, or similar tools.
• Familiarity with MLOps best practices, model versioning, monitoring, and retraining workflows.
• Exposure to hospitality, property operations, guest experience, or enterprise safety data.
• Proven ability to translate complex analytics into practical business workflows and measurable impact.

EDUCATION:
Master's degree in computer science, statistics, data science, industrial engineering, operations research, mathematics, or related field preferred. Bachelor's degree with strong relevant experience acceptable.