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Bayesian Networks Jobs in Minnesota (NOW HIRING)

Bayesian Networks information

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.

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 is the difference between Bayesian Networks vs Data Analysts?

AspectBayesian NetworksData Analysts
Required CredentialsStatistics, Data Science, Computer Science degrees; certifications in probabilistic modelingStatistics, Data Science, Business Analytics degrees; certifications in data analysis tools
Work EnvironmentResearch, modeling, and algorithm development in tech or research firmsData interpretation, reporting, and visualization across various industries
Industry UsageUsed for probabilistic reasoning, decision support, and machine learningUsed 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 popular job titles related to Bayesian Networks jobs in Minnesota? For Bayesian Networks jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Bayesian Networks jobs? Cities in Minnesota with the most Bayesian Networks job openings:

Senior Data Scientist - Marketing Sponsorships

Huntington

Minnetonka, MN

$70K - $140K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 24 days ago


Job description

Description

Overview: 

Our Enterprise Data and Analytics team is growing, and we're seeking an outstanding Senior Data Scientist to support and scale our continually expanding sponsorship portfolio. At Huntington, you will leverage machine learning, segmentation, and statistical inference on huge data sets to improve how we understand our customers and the communities we serve. Our goal is to be the Best performing Regional Bank in America, and we need data and analytics to meet that goal.

As we advance our data science and analytics capabilities, we want experts in modeling complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. The Senior Data Scientist contributes to building and developing the organization’s data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision-making processes.

Responsibilities:

  • Performs advanced analytics methods to extract value from business data
  • Performs large-scale experimentation and build data-driven models to answer business questions
  • Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence
  • Determines requirements that will be used to train and evolve deep learning models and algorithms
  • Articulates a vision and roadmap for the exploitation of data as a valued corporate asset
  • Influences product teams through presentation of data-based recommendations
  • Evangelizes best practices to analytics and products teams
  • Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring
  • Performs other duties as assigned

Basic Qualifications:

  • Master’s degree in computer science, statistics, economics or related fields
  • 1+ years' work and/or educational experience in machine learning or cloud computing, experience using statistics, machine learning, and AI to solve complex business problems, experience conducting statistical analysis with advanced statistical software, experience scripting languages, and packages, experience building and deploying predictive models, experience web scraping, and scalable data pipelines and experience with big data analysis tools and techniques.

Preferred Qualifications:

  • Up-to-date knowledge of machine learning, AI, and data analytics tools and techniques
  • Strong knowledge in predictive modeling methodology
  • Experienced at leveraging both structured and unstructured data sources
  • Willingness and ability to learn new technologies on the job
  • Demonstrated ability to communicate complex results to technical and non-technical audiences
  • Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines
  • Strategic, intellectually curious thinker with focus on outcomes
  • Professional image with the ability to form relationships across functions
  • Strong experience with R/RStudio, Python, SAS, SQL, NoSQL
  • Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)
  • Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)
  • Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling
  • Financial Services background preferred

#LI-NG1

#LI-Onsite


Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)

Yes

Workplace Type:

Office

Our Approach to Office Workplace Type

Certain positions outside our branch network may be eligible for a flexible work arrangement. We’re combining the best of both worlds:  in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Compensation Range:

$70,000-$140,000 annually

The compensation range represents the anticipated low and high end of the base compensation range for this position. Actual compensation will vary based on various factors including but not limited to location, experience, and education.  Colleagues in this position are also eligible to participate in an applicable incentive compensation plan.  In addition, Huntington provides a variety of benefits to colleagues, including health insurance coverage, wellness program, life and disability insurance, retirement savings plan, paid leave programs, paid holidays and paid time off (PTO). 

Huntington is an Equal Opportunity Employer.

Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.

Note to Agency Recruiters:  Huntington will not pay a fee for any placement resulting from the receipt of an unsolicited resume.  All unsolicited resumes sent to any Huntington colleagues, directly or indirectly, will be considered Huntington property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.