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Probabilistic Modeling Jobs in Boston, MA (NOW HIRING)

BitSight

Principal Data Scientist

Boston, MA · On-site +1

Experience with advanced ML techniques such as deep learning, GNNs, anomaly detection, or probabilistic modeling. * Experience defining or influencing ML/AI practices and strategies across the ...

OneStudyTeam

Senior Machine Learning Engineer

Boston, MA · Remote

$140K - $190K/yr

Stay up-to-date with the latest developments in ML/AI (LLMs, NLP, probabilistic modeling, etc.) and proactively bring new ideas to the team. You'll have the freedom to experiment with cutting-edge ...

MassMutual

Lead AI Engineer

Boston, MA

$172K - $225K/yr

... probabilistic modeling, with accountability for reliability, performance, and maintainability. * Design and conduct rigorous evaluations of AI system performance, including experimentation ...

New

MassMutual

AI Engineer

Boston, MA · Hybrid

$141K - $185K/yr

Design, build, and deliver end-to-end AI/ML solutions for defined business use cases, using LLMs, deep learning, agentic AI, and probabilistic modeling, with ownership of quality and performance from ...

New

Cartesian

Applied Research Scientist

Cambridge, MA · On-site

... models, probabilistic models (e.g., state estimation), SLAM, MDP, GNNs, 3D reconstruction, sensor-fusion models, ... • Publications in top-tier ML, vision, or systems venues (e.g., ACL, NeurIPS ...

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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.

Which 3 jobs will survive AI?

Probabilistic modeling is a specialized field within data science and machine learning. Jobs that require advanced analytical skills, such as data scientists, machine learning engineers, and quantitative analysts, are likely to persist as they involve complex problem-solving and domain expertise that AI tools complement rather than replace. Continuous learning and proficiency with statistical tools and programming languages like Python or R are essential for these roles.

What is probabilistic modelling?

Probabilistic modeling is a technique used in probabilistic modeling roles to represent uncertainty and variability in data through mathematical models that incorporate probability distributions. It involves designing models that can predict outcomes and infer hidden variables, often using tools like Bayesian inference and statistical analysis. These skills are essential for data scientists and statisticians working with complex, uncertain data environments.

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 professions make 500,000 a year?

In probabilistic modeling, senior roles such as quantitative researchers, data science directors, and machine learning engineers at large tech firms or financial institutions can earn $500,000 or more annually. These positions typically require advanced degrees, extensive experience, and expertise in statistical methods, programming, and data analysis tools. Compensation often includes base salary, bonuses, and stock options, especially in high-growth or competitive industries.

What professions make 200,000 a year without a degree?

Professions related to probabilistic modeling, such as data scientists, machine learning engineers, and quantitative analysts, can reach or exceed $200,000 annually often through experience, specialized skills, and industry demand. These roles typically require strong programming, statistical, and analytical skills, and some may be self-taught or gained through certifications rather than formal degrees.

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 are popular job titles related to Probabilistic Modeling jobs in Boston, MA? For Probabilistic Modeling jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Probabilistic Modeling jobs in Boston, MA look for? The top searched job categories for Probabilistic Modeling jobs in Boston, MA are:
Probabilistic Modeling jobs near you
Software Engineering Intern

Software Engineering Intern

Charles River Analytics

Cambridge, MA

$20 - $30/hr

Other

Medical

Posted 7 days ago

Job description

Charles River Analytics, a GRVTY company, creates solutions and technology to tackle the world's most challenging problems. Our team of technological entrepreneurs works together to push at the forefront of enhanced AI, robotics, smart sensing, and human-centered computing. The resulting research and development help to continuously advance government programs and discover new possibilities in the commercial marketplace. At Charles River, we take great pride in our success at attracting and retaining the most talented and creative problem-solvers in our field. Now as part of GRVTY, we offer the same trusted capabilities with increased organizational depth and expanded capacity across mission-critical national security domains. Are you ready to accelerate our mission-focused innovations? We'd love to hear from you!

This summer, we are looking for enthusiastic Software Engineering Interns for our Human-Centered AI division. We are seeking students with an interest in learning about and a successful academic background in the following areas: software engineering, computer science, machine learning, artificial intelligence, or applied mathematics. Our interns work on real projects and cutting-edge technology. We believe strongly in promoting within, which is demonstrated by the fact that we not only have hired former interns, but that several of our senior-level staff began their careers at Charles River as interns! 

You will use a variety of technologies such as machine learning, probabilistic modeling, cybersecurity, data analytics, knowledge representation, natural language processing, computational social science, and search and optimization. During your time at Charles River, you will work in small project-oriented groups of scientists and software engineers to build working prototypes in Human-Centered AI. 

What You Need:

  • U.S. Citizenship
  • Currently pursuing a graduate-level degree (M.S., PhD) in Computer Science or similar 
  • Proven proficiency in Python and a solid background in designing, programming, and documenting complex software systems
  • Demonstrated ability to rapidly learn new programming languages, technologies, and programming tools
  • Candidates should have demonstrated the capability to work independently as well as effectively within a team environment

Additional Skills:

  • Algorithms (artificial intelligence, optimization, machine learning)
  • Natural language processing
  • Probabilistic modeling and reasoning (e.g., Bayesian networks)
  • Cyber security
  • Data analytics

Salary Range

$20.00 - $30.00 per hour

The above salary range is an estimate based on the internal job level(s) for which this role is being considered. The final salary will be decided after careful evaluation of the individual's work experience, education, and overall qualifications. This range does not include the substantial total rewards, as listed below, that you will also be eligible for as an employee owner at Charles River Analytics.

Benefits:
Charles River Analytics offers an attractive benefits package that includes, but is not limited to the following:

  • Casual work environment
  • Free snacks and beverages
  • Eligible for medical plan enrollment or opt-out incentive
  • Paid sick/excused time
  • Free onsite parking and easily accessible by public transportation (the MBTA)

Internship Activities:
Interns at Charles River Analytics can participate in activities such as:

  • Intern challenge problems
  • Seminars
  • Company-wide outings

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