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Probabilistic Modeling Jobs in Texas (NOW HIRING)

Architect and develop AI-driven models for indoor localization, including fingerprinting, similarity scoring, probabilistic grid-cell prediction, and lightweight sensor fusion Understand the Physics:

Strong understanding of deep learning, reinforcement learning, computer vision, optimization, or probabilistic modeling. * Programming Skills: Proficiency in Python and deep learning frameworks ...

Strong understanding of deep learning, reinforcement learning, computer vision, optimization, or probabilistic modeling. * Programming Skills: Proficiency in Python and deep learning frameworks ...

Strong understanding of deep learning, reinforcement learning, computer vision, optimization, or probabilistic modeling. * Programming Skills: Proficiency in Python and deep learning frameworks ...

Manger, Modeling Insights

Frisco, TX · On-site

$90K - $100K/yr

Apply Bayesian and probabilistic methods to quantify uncertainty and improve decision-making. * Use ... Perform feature engineering, model evaluation, and impact measurement, clearly communicating ...

Manger, Modeling Insights

Frisco, TX · On-site

$90K - $100K/yr

Apply Bayesian and probabilistic methods to quantify uncertainty and improve decision-making. * Use ... Perform feature engineering, model evaluation, and impact measurement, clearly communicating ...

... modeling problems while collaborating across technical and business teams. This role supports ... ApplyBayesian and probabilistic methodsto quantify uncertainty and improve decision-making.

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Probabilistic Modeling information

What are the key skills and qualifications needed to thrive as a Probabilistic Modeler, and why are they important?

To thrive as a Probabilistic Modeler, you need a strong background in mathematics, statistics, and probability theory, often supported by a degree in applied mathematics, statistics, or a related field. Proficiency with programming languages like Python or R, and experience with statistical modeling tools and software such as TensorFlow or PyMC, are typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help translate complex models into actionable insights. These skills are vital for designing accurate models, interpreting uncertainty, and supporting data-driven decisions across various industries.

What are some common challenges faced by professionals in probabilistic modeling roles, and how can they be managed?

Professionals in probabilistic modeling often encounter challenges such as working with incomplete or noisy data, choosing the right model complexity, and ensuring model interpretability for stakeholders. Managing these challenges involves strong statistical knowledge, regular collaboration with domain experts, and effective communication to translate complex results for non-technical team members. Staying up-to-date with the latest tools and methodologies, and participating in peer reviews, can also help maintain model accuracy and reliability.

What is probabilistic modeling?

Probabilistic modeling is a mathematical framework used to represent uncertain events or data by using probability distributions. Instead of giving a single outcome, it accounts for variability and randomness, allowing predictions and inferences even when information is incomplete or ambiguous. Probabilistic models are widely used in fields like statistics, machine learning, finance, and engineering to analyze data, make forecasts, and support decision-making under uncertainty.

What is the difference between Probabilistic Modeling vs Data Scientist?

AspectProbabilistic ModelingData Scientist
Required CredentialsDegree in statistics, mathematics, or related fields; knowledge of probability theoryDegree in computer science, statistics, or related fields; programming skills
Work EnvironmentResearch-focused, often in analytics or data science teamsCross-functional teams, including business, engineering, and analytics
Industry UsageUsed in analytics, finance, healthcare, and research for modeling uncertaintyApplied across industries for data analysis, predictive modeling, and decision-making

Probabilistic Modeling focuses on developing models based on probability theory to understand uncertainty, while Data Scientists utilize a broader set of skills including programming, data analysis, and machine learning to extract insights from data. Both roles often overlap but serve different primary purposes within data-driven organizations.

What cities in Texas are hiring for Probabilistic Modeling jobs? Cities in Texas with the most Probabilistic Modeling job openings:
RF Modeling Manager

RF Modeling Manager

Motorola Solutions, Inc.

Richardson, TX • On-site

$140K - $170K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 hours ago


Motorola Solutions rating

8.7

Company rating: 8.7 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

12th of 137 rated electronics manufacturers


Job description

Company Overview
At Motorola Solutions, we believe that everything starts with our people. We're a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that's critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.
Department Overview
Motorola Solutions' innovations, products, and services play essential roles in people's lives. Our end-to-end suite of software solutions helps customers manage emergency communications, process video and evidence, and leverage cutting-edge AI-driven analytics for security and operational insights. We are industry leaders in video security and analytics, with solutions deployed in more than 120 countries across diverse environments such as school campuses, transportation systems, healthcare centers, public venues, critical infrastructure, prisons, factories, casinos, airports, financial institutions, government facilities, and retailers.
Our AI-powered security solutions integrate advanced video analytics, machine learning, and embedded intelligence to enable proactive threat detection, enhanced situational awareness, and automated decision-making.
Job Description
Responsibilities:
Model & Innovate: Architect and develop AI-driven models for indoor localization, including fingerprinting, similarity scoring, probabilistic grid-cell prediction, and lightweight sensor fusion
Understand the Physics: Build and refine path-loss, RF propagation, and multipath-aware models to improve accuracy, robustness, and stability
Extract the Signal: Apply advanced signal processing techniques, filtering, smoothing, noise reduction, time-series modeling to transform raw RF and IMU data into high-quality features.
Fuse Intelligence: Combine Wi-Fi RSSI, BLE RSSI, RTT timestamps, and IMU patterns to produce hybrid models that outperform single-sensor approaches.
Experiment Relentlessly: Evaluate accuracy using ground-truth traces, run controlled experiments, tune hyperparameters, and improve model confidence scoring.
Operationalize Intelligence: Deploy models into real-time scoring pipelines, collaborating with cloud engineering to ensure sub-100ms inference and large-scale reliability.
Collaborate & Elevate: Work closely with firmware, data, RF, QA, and product teams. Mentor peers in algorithmic reasoning and modeling excellence
Qualifications:
Master's degree with 6+ years of relevant work or a PhD (preferred) with 4+ years of professional experience in AI/ML, Electrical Engineering, CS, Applied Math, Robotics, or a related technical discipline.
RF & Sensors: Solid understanding of RF propagation, indoor multipath, path-loss modeling, and RTT distance estimation.
Signal Processing Specialist: Experience with filtering, Kalman/EMA smoothing, noise modeling, and time-series feature extraction.
Data Wrangler: Strong Matlab, Python skills (NumPy, SciPy, Pandas, scikit-learn) and experience working with Wi-Fi RSSI, BLE RSSI, RTT/FTM, IMU datasets.
AI/ML Engineer: Hands-on experience with clustering, probabilistic modeling, similarity metrics, and lightweight ML classification/regression.
Production Mindset: Experience deploying algorithms to real-time, enterprise-scale systems with tight latency constraints.
Algorithm Scientist Thinking: Able to analyze noisy data, design robust models, validate hypotheses, and convert prototypes into production-ready logic.
Target Base Salary Range: $140,000 - $170,000 USD
Consistent with Motorola Solutions values and applicable law, we provide the following information to promote pay transparency and equity. Pay within this range varies and depends on job-related knowledge, skills, and experience. The actual offer will be based on the individual candidate.
#LI-RS1
Basic Requirements
Master's degree with 6+ years OR a PhD with 4+ years of professional experience in AI/ML, Electrical Engineering, CS, Applied Math, Robotics, or a related technical discipline.
Travel Requirements
Under 10%
Relocation Provided
None
Position Type
Experienced
Referral Payment Plan
Yes
Our U.S. Benefits include:
  • Incentive Bonus Plans
  • Medical, Dental, Vision benefits
  • 401K with Company Match
  • 10 Paid Holidays
  • Generous Paid Time Off Packages
  • Employee Stock Purchase Plan
  • Paid Parental & Family Leave
  • and more!

EEO Statement
Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic.
We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you'd like to join our team but feel that you don't quite meet all of the preferred skills, we'd still love to hear why you think you'd be a great addition to our team.
We're committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions. To request an accommodation, please complete this Reasonable Accommodations Form so we can assist you.

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About Motorola Solutions

Sourced by ZipRecruiter

At Motorola Solutions, we believe that everything starts with safety. It's the constant that empowers people to confidently move forward. It can fill a flight or sell out a stadium. It can care for a patient or graduate a class. As a global leader in public safety and enterprise security, we create and connect the technologies that help to keep people safe where they live, learn, work and play. Our integrated technology ecosystem unifies critical communications, video security and access control, and command center software, enabling collaboration in more powerful ways. At Motorola Solutions, we're ushering in a new era in public safety and security. Bring your passion, potential and talents to a career that matters.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1928