700 Ai Computational Data Scientist jobs in Dallas,TX

New, Posted 21 hours ago

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AI Governance Operations Lead Director - RAIB

McKesson

Irving, TX 75039

~ 22 min Onsite

Degree or equivalent experience
Typically requires 12+ years of professional experience
4+ years of management experience
Proven experience designing, implementing, and scaling compliance programs for technology organizations
Strong understanding of AI laws, data protection laws and related regulatory frameworks, with the ability to translate regulatory expectations into practical enterprise workflow
AI/ML Technical Fluency
Understanding of AI/ML lifecycle, model validation, monitoring, and documentation
Familiarity with GenAI/LLM risks (hallucination, prompt injection, etc) +Knowledge of model risk management frameworks and risk‑tiering logic
Ability to influence senior stakeholders (VP/EVP level) across business units
Strong change‑leadership skills to drive adoption of governance processes

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Environmental Science Officer

United States Army

Carrollton, TX 75007

New, Posted 18 hours ago

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AML Compliance Model Developer – Associate

Santander Holdings USA

Dallas, TX 75221

Onsite

Bachelor's degree in computer science, Information Systems, Data Analytics, Finance, Mathematics, or related field
3–5 years of experience in AML Compliance Technology, AML model development, or a related field within banking or financial services
Strong programming and analytical experience using SAS for data analysis, reporting, model support, and testing
Good working knowledge of Python for data manipulation, scripting, automation, and analytical processing
Strong SQL skills with experience developing complex queries, joins, procedures, and handling large-scale datasets
Experience working with Jira for Agile project tracking, sprint management, and defect lifecycle management
Working knowledge of testing methodologies including functional testing, regression testing, SIT, and UAT
Understanding of AML regulations and compliance frameworks including BSA/AML, OFAC, KYC, and transaction monitoring concepts
Strong analytical, quantitative, and problem-solving skills
Ability to multitask, manage priorities, and work effectively in fast-paced environments
Strong communication, documentation, and stakeholder management skills
Applicants must be legally authorized to work in the United States on a full-time basis without requiring employer sponsorship to commence employment

SmartExplore AI is experimental.

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

~ 22 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

SmartExplore AI is experimental.

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Clinical Laboratory Scientist

United States Army

Garland, TX 75040

New, Posted 23 hours ago

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Salesforce Administrator

Keurig Dr Pepper

Frisco, TX 75033

~ 29 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in related field (e.g., Computer Science, Information Systems, etc.) or equivalent combination of education and work experience.
10+ years of experience as a software developer with 5+ years of experience in Consumer Goods Cloud & Retail Execution app
Salesforce Platform Developer I/II certification
Experience with Consumer Goods Cloud, Experience Cloud, and Salesforce Mobile Retail Execution App
Enterprise integration experience (Mulesoft preferred)
Exposure to large-scale user bases and mission-critical platforms
Experience supporting field sales, merchandising, or DSD-related solutions
Experience in DevOps and Agile technology environments. (preferred)

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Manufacturing Engineer

PPG

Grand Prairie, TX 75052

~ 28 min Onsite

Only US Citizens, Green card holders, political asylees, or refugees are eligible to apply
Process improvement project experience is expected.
Must have a comprehensive solid understanding of manufacturing systems and technology, or related experience commensurate with the complexity associated with the PPG Aerospace manufacturing environment.
Proven technical leadership abilities.
#LI-ONSITE
#LI-PRT1

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Oncology Account Manager/Sr. OAM - Fort Worth, TX

Genmab

Fort Worth, TX 76102

RemoteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree from an accredited institution is required.
4+ years in sales, marketing, or clinical (pharmaceutical, biotech, rare disease, or patient care) is required.
4+ years demonstrated success in Oncology sales and/or account management to be considered for Senior Oncology Account Manager
Must be proficient in the following applications: MS Word, MS Excel, MS PowerPoint, MS Outlook, MS Teams, Veeva, etc.
Must be flexible, able to manage multiple tasks, and have strong attention to detail
Ability to effectively communicate with customers, internal and external contacts at all levels
Excellent organizational, written, and verbal communication skills a must
Demonstrated commitment to operating in alignment with industry laws regulations and high ethical standards

SmartExplore AI is experimental.

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Coppell, TX 75019

~ 31 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.