Highly conversant with Bayesian type algorithms, KNN, Neural Networks, SVM, etc * Experienced in applying data science techniques on multiple industries and exposure to their sets is necessary * Data ...
Highly conversant with Bayesian type algorithms, KNN, Neural Networks, SVM, etc * Experienced in applying data science techniques on multiple industries and exposure to their sets is necessary * Data ...
Senior Machine Learning Engineer
New York, NY · On-site
$125K - $150K/yr
You will move beyond simple predictive models to build transformative algorithmic solutions using Bayesian Black Box optimization, Contextual Bandits, and Deep Q-Networks (DQN/DDQN). The problem ...
Senior Machine Learning Engineer
New York, NY · On-site
$125K - $150K/yr
You will move beyond simple predictive models to build transformative algorithmic solutions using Bayesian Black Box optimization, Contextual Bandits, and Deep Q-Networks (DQN/DDQN). The problem ...
Highly conversant with Bayesian type algorithms, KNN, Neural Networks, SVM, etc * Experienced in applying data science techniques on multiple industries and exposure to their sets is necessary * Data ...
Highly conversant with Bayesian type algorithms, KNN, Neural Networks, SVM, etc * Experienced in applying data science techniques on multiple industries and exposure to their sets is necessary * Data ...
Director - Marketing & Growth Analytics
New York, NY · On-site
$140K - $180K/yr
... cable networks AMC, BBC AMERICA, Independent Film Company, Sundance TV and We TV; and film ... Familiarity with Meridian or comparable Bayesian MMM frameworks * Substantial experience working ...
Director - Marketing & Growth Analytics
New York, NY · On-site
$140K - $180K/yr
... cable networks AMC, BBC AMERICA, Independent Film Company, Sundance TV and We TV; and film ... Familiarity with Meridian or comparable Bayesian MMM frameworks * Substantial experience working ...
Additional qualifications include: • A strong background and expertise in Bayesian statistical ... networks, and/or data and safety monitoring board statistical activities. • Experience ...
Additional qualifications include: • A strong background and expertise in Bayesian statistical ... networks, and/or data and safety monitoring board statistical activities. • Experience ...
Sr. Machine Learning Engineer, AdTech
$61.25 - $81.25/hr
Python, Algorithms, Optimisation, NLP, Data Mining, Statistical Analysis, Neural Networks ... Bayesian inference) - ML & DS (e.g., dimensionality reduction, geometry of PCA / SVD and of L1 / L2 ...
Sr. Machine Learning Engineer, AdTech
$61.25 - $81.25/hr
Python, Algorithms, Optimisation, NLP, Data Mining, Statistical Analysis, Neural Networks ... Bayesian inference) - ML & DS (e.g., dimensionality reduction, geometry of PCA / SVD and of L1 / L2 ...
Hourly Research Analyst - Rotstein Lab
Newark, NJ · On-site
$20/hr
Essential Functions: - Develop, implement and analyze bayesian / simulation-based inference algorithms and neural networks algorithms to estimate parameters in mixed-mode bursting-spiking neuronal ...
Hourly Research Analyst - Rotstein Lab
Newark, NJ · On-site
$20/hr
Essential Functions: - Develop, implement and analyze bayesian / simulation-based inference algorithms and neural networks algorithms to estimate parameters in mixed-mode bursting-spiking neuronal ...
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Nuclear Engineering Data Scientist
Lynchburg, VA · On-site
$86 - $136/hr
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Nuclear Engineering Data Scientist
Lynchburg, VA · On-site
$86 - $136/hr
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Staff RF Geolocation Engineer
Washington, DC · On-site
The company's products are powered by Coherent Distributed Networks (CDN™), empowering ... Apply statistical signal detection frameworks, including Neyman-Pearson, Bayesian, and CFAR ...
Staff RF Geolocation Engineer
Washington, DC · On-site
The company's products are powered by Coherent Distributed Networks (CDN™), empowering ... Apply statistical signal detection frameworks, including Neyman-Pearson, Bayesian, and CFAR ...
... neutral networks (DNN), recurrent neural networks (RNN), attention-based transformers, etc ... Bayesian analysis, and covariance matrices. Proficiency in agentic systems that can automatically ...
... neutral networks (DNN), recurrent neural networks (RNN), attention-based transformers, etc ... Bayesian analysis, and covariance matrices. Proficiency in agentic systems that can automatically ...
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Nuclear Engineering Data Scientist
Lynchburg, VA · Hybrid
$136K/yr
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Nuclear Engineering Data Scientist
Lynchburg, VA · Hybrid
$136K/yr
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
The company's products are powered by Coherent Distributed Networks (CDN), empowering warfighters ... Apply statistical signal detection frameworks, including Neyman-Pearson, Bayesian, and CFAR ...
The company's products are powered by Coherent Distributed Networks (CDN), empowering warfighters ... Apply statistical signal detection frameworks, including Neyman-Pearson, Bayesian, and CFAR ...
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Nuclear Engineering Data Scientist
Virginia, MN · On-site
$180 - $240/hr
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Nuclear Engineering Data Scientist
Virginia, MN · On-site
$180 - $240/hr
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
$108 - $153/hr
... networks, temporal models, self‑supervised learning) for the modality and apply representation learning under limited labels. * Statistical depth: apply survival analysis, Bayesian modeling, and ...
$108 - $153/hr
... networks, temporal models, self‑supervised learning) for the modality and apply representation learning under limited labels. * Statistical depth: apply survival analysis, Bayesian modeling, and ...
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems.
Bayesian Networks information
What is the difference between Bayesian Networks vs Data Analysts?
| Aspect | Bayesian Networks | Data Analysts |
|---|---|---|
| Required Credentials | Statistics, Data Science, Computer Science degrees; certifications in probabilistic modeling | Statistics, Data Science, Business Analytics degrees; certifications in data analysis tools |
| Work Environment | Research, modeling, and algorithm development in tech or research firms | Data interpretation, reporting, and visualization across various industries |
| Industry Usage | Used for probabilistic reasoning, decision support, and machine learning | Used for data interpretation, reporting, and business insights |
Bayesian Networks focus on probabilistic modeling and decision-making algorithms, often requiring advanced statistical knowledge. Data Analysts primarily interpret and visualize data to inform business decisions. While both roles involve data, Bayesian Networks are more technical and model-driven, whereas Data Analysts focus on data interpretation and reporting.
What are Bayesian networks?
Bayesian Networks are probabilistic graphical models that represent a set of variables and their conditional dependencies using a directed acyclic graph. They are used to model uncertainty in complex systems by encoding relationships between variables and allowing for efficient inference and reasoning. These networks are widely applied in fields such as machine learning, diagnostics, decision support, and bioinformatics to help predict outcomes and understand causal relationships.
What are the key skills and qualifications needed to thrive as a Bayesian networks specialist, and why are they important?
To thrive as a Bayesian Networks Specialist, you need a strong background in statistics, probability theory, and machine learning, often supported by a degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, and experience using specialized libraries like pgmpy or bnlearn, are typically required. Strong analytical thinking, problem-solving ability, and effective communication skills set standout professionals apart in this role. These competencies are crucial for designing, implementing, and interpreting Bayesian models that inform critical decision-making in complex domains.
What are some common challenges faced by professionals working with Bayesian networks in real-world projects?
Professionals working with Bayesian Networks often encounter challenges such as handling incomplete or noisy data, defining accurate conditional dependencies, and ensuring computational efficiency for large or complex networks. Collaboration with domain experts is crucial to correctly structure the network and validate assumptions. Additionally, integrating Bayesian models with existing data systems and effectively communicating probabilistic results to non-technical stakeholders are important aspects of the role.
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Job description
Company Description
SRP is a big data startup company located in Princeton, NJ focused on Dynamic Pricing, run
by seasoned alumni from Stanford University and Wharton (UPenn).
Job Description
Title: Senior Data Scientist for a Startup
Location: Princeton, NJ
Full Time
Job Requirements:
- A minimum of three years of experience working as a data scientist
- Experience in working with large data sets
- Strong experience in machine learning
- Highly conversant with Bayesian type algorithms, KNN, Neural Networks, SVM, etc
- Experienced in applying data science techniques on multiple industries and exposure to their sets is necessary
- Data cleanup, and data massaging experience
- Hands-on experience with Python / R type languages
- Any experience in doing well at Kaggle type competitions is a big plus
- PhD is a big plus
Additional Information
This is a Full time project
About SRP Systems
Sourced by ZipRecruiter
Industry
Software development
Company size
11 - 50 Employees
Headquarters location
Princeton, NJ, US
Year founded
2007