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Machine Learning Quantum Computing Jobs in Houston, TX

NAVA Software Solutions

Lead Data Scientist

Houston, TX · On-site

Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). * Strong understanding of the Machine Learning lifecycle - feature engineering, training ...

Rice University

Research Scientist

Houston, TX · On-site

$80K/yr

Brown School of Engineering and Computing The George R. Brown School of Engineering and Computing ... machine learning, or deep learning algorithms. * Familiarity with clinical imaging workflows ...

Deloitte

Senior AI Engineer - SFL Scientific

Houston, TX

$99K - $137K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... using cloud computing or on-prem technologies * Design and lead development on scalable, high ...

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All JobsMachine Learning Quantum Computing JobsMachine Learning Quantum Computing Jobs in Houston, TX

Machine Learning Quantum Computing information

See Houston, TX salary details

$24.4K

$40.7K

$84K

How much do machine learning quantum computing jobs pay per year?

As of Jul 12, 2026, the average yearly pay for machine learning quantum computing in Houston, TX is $40,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,000.00 and $43,900.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Quantum Computing vs Data Scientist?

AspectMachine Learning Quantum ComputingData Scientist
Required CredentialsAdvanced degrees in quantum computing, machine learning, or related fieldsDegree in data science, statistics, or computer science
Work EnvironmentResearch labs, tech companies focusing on quantum tech, academiaBusiness environments, tech companies, consulting firms
Industry UsageEmerging quantum tech industry, research institutionsFinance, healthcare, marketing, e-commerce
Common Search/ComparisonQuantum algorithms, quantum machine learningData analysis, predictive modeling

Machine Learning Quantum Computing specialists focus on developing algorithms that leverage quantum mechanics to enhance machine learning tasks, often requiring advanced knowledge of quantum physics. Data Scientists analyze and interpret large datasets using traditional machine learning techniques. While both roles involve machine learning, the former emphasizes quantum computing applications, whereas the latter centers on data analysis in conventional computing environments.

What are the key skills and qualifications needed to thrive as a Machine Learning Quantum Computing Specialist, and why are they important?

To thrive in Machine Learning Quantum Computing, you need strong foundations in quantum mechanics, linear algebra, and advanced machine learning concepts, typically supported by a degree in physics, computer science, or a related field. Familiarity with quantum programming languages (such as Qiskit or Cirq), cloud-based quantum platforms, and proficiency in Python are usually required, alongside experience with relevant certifications or coursework. Strong problem-solving skills, adaptability, and effective collaboration are vital soft skills in this interdisciplinary field. These competencies are crucial for driving innovation and bridging the gap between quantum computing and practical machine learning applications.

How do professionals in Machine Learning Quantum Computing typically collaborate with interdisciplinary teams?

Professionals in Machine Learning Quantum Computing often work closely with experts in physics, computer science, and engineering. Collaboration usually involves translating quantum concepts for machine learning specialists and vice versa, ensuring that algorithms are both theoretically sound and practically implementable on quantum hardware. Regular meetings, code reviews, and knowledge-sharing sessions are standard, as interdisciplinary insight is crucial for advancing research and developing scalable solutions. Effective communication and a willingness to learn from other domains are essential for success in these teams.

What is Machine Learning Quantum Computing?

Machine Learning Quantum Computing is an interdisciplinary field that combines principles of quantum computing with machine learning techniques. It aims to leverage the computational power of quantum computers to enhance the performance of machine learning algorithms, potentially solving complex problems more efficiently than classical computers. This area includes developing quantum algorithms for tasks such as classification, clustering, and optimization, as well as using machine learning to improve quantum hardware and error correction. Researchers expect that, as quantum hardware matures, this field could revolutionize data analysis, cryptography, and scientific discovery.
What are popular job titles related to Machine Learning Quantum Computing jobs in Houston, TX? For Machine Learning Quantum Computing jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Quantum Computing jobs in Houston, TX look for? The top searched job categories for Machine Learning Quantum Computing jobs in Houston, TX are:
What cities near Houston, TX are hiring for Machine Learning Quantum Computing jobs? Cities near Houston, TX with the most Machine Learning Quantum Computing job openings:
Machine Learning Quantum Computing jobs near you
Lead Data Scientist

Lead Data Scientist

NAVA Software Solutions

Houston, TX • On-site

Full-time

Posted 26 days ago

Job description

NAVA Software solutions is looking for a Lead Data Scientist
Details:
Lead Data Scientist
Location: Houston TX - 4 days onsite
Duration: Full time /Direct Hire
The Lead Data Scientist will spearhead the design, development, implementation and maintenance and improvement of advanced data science initiatives across business units, directly aligning with strategic objectives. This role encompasses transforming innovative ideas into real-world solutions through the application of sophisticated analytical techniques such as machine learning, optimization, and cluster analysis.
The incumbent will lead and help to develop a newly formed data-scientists taskforce in delivering impactful analytical solutions, ensuring these innovations are seamlessly embedded into business operations to drive decision-making, enhance operational efficiency, and foster a culture of continuous improvement and innovation. As part of this role the applicant will play a significant part in setting the AI & ML agenda for The Friedkin Group, including working with business units to define potential opportunities, and defining standards and best practice for AI & ML at TFG
ESSENTIAL FUNCTIONS
  • Translates business needs into analytics/reporting requirements to support data-driven decisions with required information & explain ability.
  • Keep abreast of the latest data science techniques and technologies. Explore and implement innovative solutions to improve data analysis, modeling capabilities, and business outcomes.
  • Communicate complex data insights in a clear and effective manner to stakeholders across the organization, including non-technical audiences. Advocate for the importance and value of data-driven decision making.
  • Manage use case design and build teams on day-to-day basis, providing guidance and feedback as they develop and operationalize data science models and algorithms to solve complex business problems.
  • Ensure analytical insights and products are embedded into business processes.
  • Ensure use case models/analytics are supported, maintained, and improved (as needed) post-development and launch.
  • Guide and sign off on analytics/modelling approach, model deployment requirements, and quality assurance standards with input from use case teams and business leadership.
  • Provide input to the long/term plan for TFGs Data Science team, including key focus areas, talent acquisition, input to technology platforms, and interaction model with the rest of the organization.
  • Foster a culture of innovation and continuous improvement and lead the exploration and adoption of new data science technologies and methodologies to contribute to the advancement of TFG's analytics expertise.
  • Work with wide landscape of business and technical stakeholders to proactively identify applicable new technologies and opportunities and detail and communicate how they can deliver measurable business value.
  • Own the analytics solution portfolio, including model maintenance and improvements over time.

SUPERVISORY RESPONSIBILITIES
  • Directly supervises one or more employees. Carries out responsibilities in accordance with the organization's policies and applicable laws.
  • Demonstrated ability to lead and manage data science projects, including, managing workflow and priorities, to ensure timely delivery of projects with high-quality outcomes.
  • Proven track record of recruiting, training, and retaining a skilled data science team, identifying talent gaps, and addressing them.

QUALIFICATIONS
  • A master's degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field, with at least 5 - 7 years' experience in data science or a similar role.
  • Proficient in at least one analytical programming language relevant for data science. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI).
  • Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, pattern recognition, cluster analysis, etc.)
  • Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark).
  • Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.
  • Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.,
  • Good understanding of programming best practices, building for re-use and highly automated CI/CD pipelines.

SOFT SKILLS
  • Proven track record of leading cross-functional teams to successfully deliver complex data-driven projects.
  • Excellent problem-solving and analytical skills, with the ability to translate complex technical details into understandable business insights.
  • Sees overall 'picture' and alternative approaches and develop vision of what may be possible.
  • Strong interpersonal and communication skills, capable of working effectively with and developing trust from both non-technical and technical counterparts to influence key use case & enterprise decisions.

CERTIFICATES, LICENSES, REGISTRATIONS*
  • Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous.
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About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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