Principal Data Scientist (Remote)
Lansing, MI · On-site +1
Ensures ongoing model health through post-deployment monitoring, drift detection, and audit ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Principal Data Scientist (Remote)
Lansing, MI · On-site +1
Ensures ongoing model health through post-deployment monitoring, drift detection, and audit ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Ensures ongoing model health through postdeployment monitoring, drift detection, and auditcompliant ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Ensures ongoing model health through postdeployment monitoring, drift detection, and auditcompliant ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Principal Data Scientist (Remote)
Lansing, MI · On-site +1
Ensures ongoing model health through post-deployment monitoring, drift detection, and audit ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Principal Data Scientist (Remote)
Lansing, MI · On-site +1
Ensures ongoing model health through post-deployment monitoring, drift detection, and audit ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Ensures ongoing model health through postdeployment monitoring, drift detection, and auditcompliant ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Ensures ongoing model health through postdeployment monitoring, drift detection, and auditcompliant ... Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
Senior Machine Learning Engineer
Detroit, MI · On-site +1
$126K - $180K/yr
... and monitoring. * Establish and refine best practices in our ML system architecture, CI/CD ... White-box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural ...
Senior Machine Learning Engineer
Detroit, MI · On-site +1
$126K - $180K/yr
... and monitoring. * Establish and refine best practices in our ML system architecture, CI/CD ... White-box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural ...
Remote Neural Monitoring information
What jobs in the US pay $300,000 a year?
Remote Neural Monitoring is a specialized field that typically involves advanced skills in neuroscience, cybersecurity, and data analysis. High-paying roles in related fields, such as senior AI researchers, data scientists, or cybersecurity executives, can reach or exceed $300,000 annually, especially with extensive experience, certifications, and leadership responsibilities. These positions often require advanced degrees and a strong track record in technology or research environments.
What is remote neuromonitoring?
Remote neuromonitoring involves monitoring brain activity and neural functions from a distance, often using specialized equipment and software. In a job context, roles may require knowledge of neuroscience, signal processing, and remote communication tools to assess neurological health or performance remotely.
What are the key skills and qualifications needed to thrive in the Remote Neural Monitoring position, and why are they important?
To thrive as a Remote Neural Monitoring Specialist, you need an advanced understanding of neuroscience, electrophysiology, and experience with neural data acquisition, typically supported by a relevant degree in biomedical engineering, neuroscience, or a related field. Familiarity with brain-computer interface (BCI) systems, neural data analysis software, and compliance with institutional review board (IRB) protocols or other regulatory standards is essential. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical information clearly set top candidates apart. These skills ensure accurate data interpretation, adherence to ethical standards, and effective collaboration within interdisciplinary research or clinical teams.
What are the primary responsibilities and challenges faced by a Remote Neural Monitoring Specialist?
As a Remote Neural Monitoring Specialist, your primary responsibilities include continuously tracking neural activity data from patients or research subjects, ensuring the integrity and quality of data, and providing real-time feedback to clinical or research teams. One of the main challenges in the role is accurately identifying significant neural events or anomalies while minimizing false positives, which requires both technical expertise and focused attention. You may also need to troubleshoot technical issues with monitoring equipment or software remotely and maintain strict compliance with privacy and ethical guidelines. Collaboration with physicians, neuroscientists, or IT professionals is common, ensuring comprehensive care or data analysis. This role offers opportunities to advance into project management, clinical lead positions, or specialize in emerging neurotechnology fields.
What is a Remote Neural Monitoring job?
Remote Neural Monitoring (RNM) is a concept often associated with surveillance theories rather than an established job role. It is sometimes described as technology that can remotely track neural activity, but there is no verified scientific basis for such a profession. If you're looking for careers in neuroscience, artificial intelligence, or brain-computer interfaces, consider roles in neurotechnology research, cognitive science, or biomedical engineering. Always verify job listings with reputable sources to avoid misinformation.
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Remote Neural Monitoring is a specialized field that often involves technical skills, attention to detail, and problem-solving. Jobs suited for ADHD brains typically include roles with flexible schedules, hands-on tasks, or creative elements, such as data analysis, technical support, or content creation. These roles can help maintain focus and engagement while accommodating different working styles.
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Remote neural monitoring is a controversial and largely unregulated technology that claims to read or influence brain activity remotely. Currently, there are no specific laws explicitly permitting or prohibiting its use, and ethical and legal concerns remain significant. Employment in this field often requires understanding of privacy laws and ethical standards related to neurotechnology.
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Full-time
Posted just now
Job description
SUMMARY
AF Group is seeking a Principal Data Scientist with expertise in either Commercial Property or Personal Homeowners insurance to serve as an individual contributor and technical authority on applying advanced analytics and machine learning to complex business problems, including pricing, risk selection, and other underwriting challenges. This role owns the end-to-end analytical lifecycle, from problem formulation and model development through deployment, monitoring, and governance. Partners closely with Actuarial, MLOps, and IT to deliver scalable, production-ready solutions. The Principal Data Scientist ensures long-term model performance through rigorous validation, drift monitoring, and audit-ready documentation, while advancing analytical best practices and evaluating emerging techniques relevant to commercial P&C insurance.
RESPONSIBILITIES/TASKS:
- Acquires, organizes, and cleanses structured and unstructured data.
- Conducts in-depth analysis to uncover trends, risks, and business opportunities.
- Applies statistical modeling, machine learning, and advanced analytics to develop predictive and prescriptive solutions.
- Evaluate solution performance using statistically rigorous methods and measure the impact to business outcomes.
- Collaborate with MLOps and IT partners to transition solution prototypes from pilot validation into production environments.
- Ensures ongoing model health through post-deployment monitoring, drift detection, and audit-compliant governance practices.
- Creates and communicates results to senior level audiences of varying backgrounds, using business-facing presentations, reports, and dashboards.
- Author and maintain comprehensive technical documentation for data lineage, codebases, results, and production changes.
- Provides technical and project guidance, including peer review of work, for data science team.
- Leads the evaluation of new analytic tools and processes.
- Drives investigation and adoption of advanced machine learning and AI innovations.
EDUCATION:
Bachelor's Degree in Data Science, Statistics, Mathematics, Operations Research, Actuarial Science, Computer Science, Engineering, Physics or related technical field required. Advanced degree preferred.
EXPERIENCE:
10 years of experience in data science or related advanced analytics domains, including research and teaching, with 3+ years of technical leadership.
REQUIRED SKILLS/KNOWLEDGE/ABILITIES
- 3+ years of experience supporting underwriting functions, including loss modeling, for Commercial Property (preferred) or Personal Homeowners insurance.
- Demonstrated expertise using Poisson, Gamma, and Tweedie distributions to build loss ratio, pure premium, and frequency-severity loss models for pricing.
- Extensive experience leveraging supervised learning models (e.g., XGBoost, GLM, etc.) and unsupervised techniques (e.g., K-means, PCA, etc.) to solve complex data science problems.
- Advanced Python programming skills supporting data science, including scikit-learn and pandas.
- Proficient data wrangling and ETL abilities using SQL on relational databases.
- Comfortable explaining machine learning models with partial dependence plots and SHAP values.
- Ability to conduct experiments e.g., A/B Testing, to evaluate the causal impact of model-driven decisions.
- Experience using version control tools such as Git and Azure DevOps.
- Experience working in cloud computing environments such as Azure, AWS, GCP, etc.
PREFERRED SKILLS/KNOWLEDGE/ABILITIES
- Experience supporting at least one other commercial or personal line outside of Property lines.
- In-depth understanding of General Liability (aka Casualty), Workers Compensation, or Commercial Vehicle insurance.
- Knowledge of actuarial concepts and terminology used in pricing and ratemaking.
- Experience with Claims, Marketing, or Operations functions within P&C insurance settings.
- Ability to develop Agentic AI solutions to drive autonomous decision-making and task orchestration.
- Familiarity with causal modeling techniques such as Meta-learners, Causal Forest, Double ML, etc.
- Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
- Understanding of NLP concepts such as topic modeling, Word2Vec, sentiment analysis, OCR, etc.
- Experience programming in the R language.
- Ability to build interactive dashboards using frameworks such as Plotly Dash, Power BI, Flask, etc.
ADDITIONAL INFORMATION:
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. This job description does not constitute a contract for employment.
PAY RANGE:
"Actual compensation decision relies on the consideration of internal equity, candidate's skills and professional experience, geographic location, market and other potential factors. It is not standard practice for an offer to be at or near the top of the range, and therefore a reasonable estimate for this role is between $137,900 and $231,000."
We are an Equal Opportunity Employer. We will not tolerate discrimination or harassment in any form. Candidates for the position stated above are hired on an "at will" basis. Nothing herein is intended to create a contract.
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