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Data Science Bank Jobs in Nevada (NOW HIRING)

SynergisticIT

Junior Data/BI Analyst

Carson City, NV · On-site

... Paypal, Banking, Wayfair, Client, Client and hundreds more with Job offers of $95k to $154k ... We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts ...

Credit One Bank

Sr. Financial Manager

Las Vegas, NV · Hybrid

$105K - $143K/yr

This is a hybrid financial analysis / data science position. The Products team is responsible for ... Collaborate with key stakeholders from across the bank Position Requirements * Bachelor's degree in ...

Credit One Bank

Sr. Financial Manager

Las Vegas, NV · Hybrid

$105K - $143K/yr

This is a hybrid financial analysis / data science position. The Products team is responsible for ... Collaborate with key stakeholders from across the bank Position Requirements * Bachelor's degree in ...

CreditOne

AVP, Artificial Intelligence

Las Vegas, NV · On-site

... AI/ML or data science. * Experience working with large-scale financial or transactional data is preferred. Credit One Bank, N.A. is a data-driven financial services company based in Las Vegas.

Credit One Bank

Lead Financial Analyst

Las Vegas, NV · Hybrid

This is a hybrid financial analysis/data science position. The Products team is responsible for ... Collaborate with key stakeholders from across the bank Position Requirements: * Bachelor's degree ...

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How much do data science bank jobs pay per year?

As of Jul 29, 2026, the average yearly pay for data science bank in Nevada is $124,985.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,300.00 and $138,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist in banking, and why are they important?

To thrive as a Data Scientist in banking, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with programming languages like Python or R, experience with machine learning libraries, and knowledge of data visualization and big data platforms such as SQL, Hadoop, or Spark are crucial. Exceptional problem-solving abilities, attention to detail, and effective communication skills help you translate complex data insights into actionable strategies for non-technical stakeholders. These skills ensure accurate risk assessment, fraud detection, and data-driven decision-making in the highly regulated financial sector.

What is the role of data science in banking?

Data science in banking involves analyzing large datasets to improve decision-making, detect fraud, assess credit risk, and personalize customer services. Data scientists use tools like machine learning and statistical models to optimize operations and develop predictive insights within the financial environment.

Do data scientists work at banks?

Yes, data scientists work at banks to analyze financial data, develop predictive models, and improve decision-making processes. They often use tools like Python, R, and SQL and may require knowledge of finance and machine learning techniques.

What does a Data Science professional do in a bank?

A Data Science professional in a bank leverages data analysis, statistical modeling, and machine learning to solve business problems and improve decision-making. Their work often involves analyzing customer behavior, detecting fraud, assessing credit risk, and optimizing marketing strategies. They collaborate with other departments to turn raw data into actionable insights, ensuring the bank remains competitive and compliant with regulations. By building predictive models and dashboards, they help the bank enhance efficiency, profitability, and customer satisfaction.

What is the salary of a bank data scientist?

A bank data scientist typically earns between $80,000 and $130,000 annually, depending on experience, location, and education. Senior roles or those with specialized skills in machine learning and big data tools can earn higher salaries, often exceeding $150,000.

Is 40 too late for data science?

Data science roles are open to candidates of all ages, and many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

How does a Data Scientist at a bank typically contribute to cross-functional teams, and what collaboration challenges might they face?

As a Data Scientist in a banking environment, you will frequently collaborate with teams from IT, risk management, marketing, and business strategy to develop data-driven solutions. This might involve translating complex analytical findings into actionable insights for non-technical stakeholders or integrating models into existing business processes. Common challenges include aligning data science objectives with business goals, managing data privacy concerns, and ensuring clear communication across different departments. Building strong relationships and maintaining open communication channels are essential for overcoming these challenges and delivering impactful results.
What are popular job titles related to Data Science Bank jobs in Nevada? For Data Science Bank jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Data Science Bank jobs in Nevada look for? The top searched job categories for Data Science Bank jobs in Nevada are:
Data Science Bank jobs near you
Infographic showing various Data Science Bank job openings in Nevada as of July 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 92% Physical, 4% Hybrid, and 4% Remote job distribution, with an average salary of $124,985 per year, or $60.1 per hour.
AVP, Artificial Intelligence

AVP, Artificial Intelligence

Credit One Bank

Las Vegas, NV • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Position Summary
The Assistant Vice President of Artificial Intelligence (AVP of AI) is responsible for leading delivery and execution of AI and machine learning capabilities within a regulated banking, credit card, and financial services environment. Reporting to the VP of AI, this role acts as a hands-on technical leader and people manager for AI Engineers, ensuring AI solutions drive fraud prevention, credit risk management, customer experience personalization, and operational efficiency while meeting regulatory, privacy, and model risk requirements.
Essential Job Functions
  • Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
  • Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
  • Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
  • Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
  • Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
  • Oversee model validation, explainability, bias testing, and audit readiness.
  • Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.
Position RequirementsCore AI Concepts and Technologies Required:
  • Machine Learning & Modeling
    • Supervised, unsupervised, reinforcement learning
    • Deep learning (CNNs, RNNs, Transformers)
    • Natural Language Processing (NLP) & LLMs
    • Generative AI (diffusion models, fine-tuning, RAG)
    • AI Engineering & MLOps
  • AI Engineering & MLOps
    • Model training, deployment, monitoring, and retraining
    • Feature stores, vector databases, and model registries
    • CI/CD pipelines for ML (MLOps)
    • GPU/accelerator compute architectures
  • Cloud & Infrastructure
    • Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI
    • Kubernetes, containerization, microservices
    • Data platforms (Databricks, Snowflake, Synapse)
  • Responsible AI & Governance
    • Model explainability (SHAP, LIME)
    • Fairness, bias detection, model risk controls
    • Privacy-preserving ML techniques (differential privacy, federated learning)
  • Programming & Tooling
    • Python, PyTorch, TensorFlow, JAX
    • LangChain, semantic search, vector embeddings
    • Prompt engineering & LLM orchestration frameworks
  • Excellent communication, problem-solving, and project management skills
  • Ability to collaborate effectively and follow up ensure achievement of deadlines, outcomes and results.
  • Demonstrate company core values of excellence, ownership, collaboration, and integrity.
Preferred
  • Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
  • 5-8 + years of experience in AI/ML or data science.
  • Experience working with large-scale financial or transactional data is preferred.
Credit One Bank, N.A. is a data-driven financial services company based in Las Vegas. Founded in 1984, Credit One Bank offers a spectrum of credit card products for people in all stages of financial life. Credit One Bank is an equal opportunity employer committed to diversity and inclusion and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation, or national origin. Reasonable accommodations can be made for those who require them, including access to job applications and workplace accommodations. Employment at Credit One Bank is based on mutual consent (also known as at-will). This means that employees and the Bank may terminate the employment relationship at any time, with or without cause and with or without notice. Please contact the recruiter for this position to learn more. Credit One Bank does not accept unsolicited resumes from agencies and is not responsible for related fees.