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Probabilistic Modeling Jobs in Georgia (NOW HIRING)

Fisec Global

Gen AI Engineer

Atlanta, GA · On-site

Strong background in machine learning, deep learning, and probabilistic modeling. * Proficiency in modern data science tools and frameworks, such as PyTorch, Tensorflow, JAX, Scikit-learn, and Keras.

Warnerbros

Sr. Principal Data Scientist

Atlanta, GA

Time-series forecasting & probabilistic models * Causal inference, experimentation & uplift modelling * NLP, generative AI & multimodal ML systems * Computer vision & video intelligence pipelines

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection. * Background in Daily Fantasy Sports (DFS), oddsmaking, or ...

Tekwissen

Senior AI/ML Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Design and lead end-to-end identity resolution architecture, combining probabilistic models, ML, and embedding-based techniques to build the authoritative customer identity graph. * Build and ...

AEG Presents

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection. * Background in Daily Fantasy Sports (DFS), oddsmaking, or ...

AEG

Staff Machine Learning Engineer

Atlanta, GA · On-site

$220K - $280K/yr

Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection. * Background in Daily Fantasy Sports (DFS), oddsmaking, or ...

Ditto

$128K - $260K/yr

Modern probabilistic data structures such as bloom filters and cuckoo filters. * Highly concurrent ... Experience with lightweight formal methods such as property testing and model checking.

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Probabilistic Modeling information

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 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 probabilistic modelling?

Probabilistic modeling is a technique used in probabilistic modeling roles to develop mathematical models that incorporate uncertainty and randomness. It involves using statistical methods and tools like Bayesian inference or Markov processes to analyze data and make predictions. Professionals in this field often work with programming languages such as Python or R and require strong analytical skills.

What jobs make $1,000,000 a year?

In the field of probabilistic modeling, highly experienced data scientists, machine learning engineers, or quantitative researchers working in finance, hedge funds, or tech companies can earn $1,000,000 or more annually. These roles often require advanced degrees, specialized skills in statistical analysis and programming, and experience with large-scale data and modeling tools. Compensation at this level typically includes base salary, bonuses, and equity components.

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 jobs pay 500,000 a year in the US?

In the field of probabilistic modeling, senior roles such as Lead Data Scientist or Quantitative Research Director can reach or exceed $500,000 annually, especially in finance, technology, or consulting firms. These positions typically require advanced skills in statistical analysis, machine learning, and programming, along with extensive experience and often a master's or Ph.D. degree.

What jobs make $10,000 a month without a degree?

In probabilistic modeling and related data science roles, professionals can earn $10,000 or more monthly through freelance consulting, specialized contract work, or high-demand positions in finance, tech, or analytics that value skills over formal degrees. Success often depends on expertise in statistical software, programming languages like Python or R, and a strong portfolio of projects. Building a reputation and gaining experience can lead to high earnings without a traditional degree.

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.
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Probabilistic Modeling jobs near you
Lead Data Scientist, Appraisal & Pricing

Lead Data Scientist, Appraisal & Pricing

Amplio

Atlanta, GA

Other

Medical, Dental, Vision, PTO

Posted 24 days ago

Job description

About the Role

Amplio is building the intelligence layer that powers how manufacturers recover value from surplus equipment. You'll lead the development of our appraisal and pricing capabilities - combining data science with agentic AI to automate and improve valuation decisions at scale.

Key Responsibilities

  • Design and iterate models that estimate fair market value, recovery potential, and optimal disposition strategy.
  • Leverage agentic AI to automate cataloging and appraisal workflows.
  • Support Sales to underwrite buyout offers and predict consignment recovery and capacity utilization.
  • Build feedback loops for continuous price optimization and model refinement.
  • Collaborate with Product and Ops to turn insights into high-impact pricing and sourcing actions.

Requirements

What You Bring

  • 4-8+ years in data science, analytics, or preferably pricing within marketplaces, logistics, or asset-heavy environments.
  • Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling).
  • Comfort operating with limited data - capable of building and validating proxy-based models.
  • Blend of technical depth and business intuition; fluent in assumptions, risk, and real-world tradeoffs.
  • Curiosity for manufacturing, recommerce, and the circular economy.

Benefits

  • Early-hire equity
  • Best Medical / Dental / Vision plans
  • Parental benefits
  • Flexible PTO
  • Various stipends
  • Clear work-life boundaries

Apply