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Dataiku Jobs in Texas (NOW HIRING)

Senior Data Scientist

Austin, TX · On-site

$120K - $180K/yr

Experience with Dataiku and Google Cloud ie: Vertex AI, Big Query * Expertise in MLops and model monitoring * Familiarity working in regulated environments Skill Development Values At Schwab, we ...

Support Engineer

Austin, TX · On-site

$120 - $150/hr

Familiarity with data science tooling such as Dataiku, Snowflake, Airflow, or Python-based analytics pipelines. * Experience with full-stack web frameworks, including Node.js/Express.js, Apollo ...

Support Engineer

Austin, TX · On-site

$184K - $277K/yr

Familiarity with data science tooling such as Dataiku, Snowflake, Airflow, or Python-based analytics pipelines. Experience with full-stack web frameworks, including Node.js/Express.js, Apollo GraphQL ...

Experience with Dataiku and Google Cloud ie: Vertex AI, Big Query * Expertise in MLops and model monitoring * Familiarity working in regulated environments Skill Development Values At Schwab, we ...

Familiarity with data science tooling such as Dataiku, Snowflake, Airflow, or Python-based analytics pipelines. Experience with full-stack web frameworks, including Node.js/Express.js, Apollo GraphQL ...

Showing results 21-39

Dataiku information

See Texas salary details

$2.2K

$4.1K

$7.7K

How much do dataiku jobs pay per month?

As of Sep 3, 2026, the average monthly pay for dataiku in Texas is $4,122.58, according to ZipRecruiter salary data. Most workers in this role earn between $3,025.00 and $4,658.33 per month, depending on experience, location, and employer.

What is a Dataiku?

A Dataiku job typically involves working with Dataiku DSS, a collaborative data science and machine learning platform used for analytics, automation, and AI development. Roles can vary from data engineers and data scientists to machine learning engineers and analytics professionals who use Dataiku to build, deploy, and manage data workflows. Responsibilities may include data preparation, model training, automation, and integrating Dataiku with other enterprise systems. Companies use Dataiku to streamline AI and analytics processes, improving decision-making and operational efficiency. Proficiency in Dataiku, Python, SQL, and machine learning concepts is often required for these roles.

What are the typical day-to-day responsibilities for someone working with the Dataiku platform?

Professionals working with the Dataiku platform spend much of their day building and maintaining data pipelines, collaborating with stakeholders to define business requirements, developing and deploying machine learning models, and ensuring data quality. They also use Dataiku DSS to automate workflows, prepare datasets, and visualize analytical results. Regular communication with data engineers, business analysts, and management is essential to align data projects with organizational goals. The role often involves troubleshooting technical challenges and staying current with platform updates and best practices.

What are the key skills and qualifications needed to thrive in the Dataiku position, and why are they important?

To excel as a Dataiku Data Scientist or Platform Specialist, you typically need a strong background in data analysis, machine learning, and programming languages such as Python or R, often supported by a degree in computer science, statistics, or a related field. Experience with the Dataiku Data Science Studio (DSS) platform, plus relevant certifications like Dataiku DSS Associate or Designer, is highly valued. Strong problem-solving skills, effective communication, and teamwork are important soft skills to succeed in this role. These abilities ensure that data solutions are effectively designed, implemented, and communicated within cross-functional teams, driving successful business outcomes.

What does Dataiku do?

Dataiku is a company that provides a data science platform enabling data analysts and scientists to build, deploy, and manage machine learning models and data workflows. It offers tools for data preparation, visualization, and collaboration, often used in environments requiring knowledge of data analytics and programming skills. The platform supports integration with various data sources and programming languages like Python and R.

What are the most commonly searched types of Dataiku jobs in Texas?

The most popular types of Dataiku jobs in Texas are:

What are popular job titles related to Dataiku jobs in Texas?

For Dataiku jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Dataiku jobs in Texas look for?

The top searched job categories for Dataiku jobs in Texas are:

What cities in Texas are hiring for Dataiku jobs?

Cities in Texas with the most Dataiku job openings:

Infographic showing various Dataiku job openings in Texas as of August 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $49,471 per year, or $23.8 per hour.

Senior Data Scientist

Charles Schwab Inc.

Austin, TX • On-site

$120K - $180K/yr

Full-time

Posted 12 days ago


Job description

Your Opportunity
At Schwab, you have the opportunity to do meaningful work that helps clients take control of their financial futures. You'll be part of a collaborative, technology-forward environment that values curiosity, continuous learning, and thoughtful problem-solving. Schwab Technology Services (STS) enables innovative and reliable technology products that power how clients manage their money, supporting Schwab's commitment to expanding access to investing and financial planning. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
Organization / Role Description
Schwab's AI & Data Science organization is a centralized hub for delivering innovative production ready AI and machine learning solutions that drive measurable business outcomes across the firm. The team partners with Schwab business units to identify high impact use cases, pilot innovative AI solutions, and transition successful models into enterprise level production systems. Our mission is to accelerate the adoption of AI as a strategic product capability-ensuring models are scalable, reusable, governable, and continuously delivering value.
As a data scientist, you will play an essential part in advancing Schwab's capabilities by driving the design, development, and implementation of innovative AI and machine learning solutions that address complex, enterprise scale challenges. You'll bridge advanced research and robust engineering, owning the end-to-end lifecycle of high-impact models. Successful candidates will work collaboratively across the organization with our business sponsors, development teams, and engineering partners. We are seeking a subject matter expert in all things AI, primed to identify and translate advanced analytical techniques, applications, and strategies into practical production ready solutions.
What You'll Do
The Data Scientist will work collaboratively with a team of data scientists, ML engineers, and product owners throughout a project lifecycle, including data extraction and preparation, feature engineering, model design and development and everything in between- this is a role that will requires hands on expertise to create value adding solutions that solve real business problems.
This role supports multiple business units across Schwab from enterprise services such as Marketing to client and product groups like Investor and Advisor Services.
What you bring
Machine Learning: Knowledge of and experience with designing and implementing algorithms (Gradient Boosting Trees, GLM/Regression, Random Forest, Neural Networks, K-Means clustering etc.), and the ability to articulate their real-world advantages and drawbacks.
LLMs: Experience with modern large language models from usage for embeddings and classification to agentic frameworks. Familiarity on evals and measurement frameworks.
Statistical Methodology: Knowledge of advanced techniques and concepts (regression, properties of distributions, time series analysis and modeling, statistical tests and proper usage, etc).
Business Acumen: Understanding the bigger picture for customers and the business and the know how to probe beyond stakeholders' stated requests to understand what is truly needed to capture and drive business value.
What you have
Required Qualifications
  • MS/PHD in a quantitative field (eg. Statistics, Mathematics, Computer Science, Engineering, Physics, Operations Research, etc).
  • Demonstrated professional experience in delivering production AI and Data Science products
  • Strong foundational knowledge of:
    • Statistics and probability
    • Machine learning fundamentals (regression, classification, clustering)
  • Proficiency in Python and software engineering methodologies
  • Strong verbal and written communication skills
  • Self-starter with strong organizational skills, attention to detail, and desire to continually reevaluate existing products and processes.

Preferred Qualifications
  • Experience with Dataiku and Google Cloud ie: Vertex AI, Big Query
  • Expertise in MLops and model monitoring
  • Familiarity working in regulated environments

Skill Development Values
At Schwab, we believe growth happens through continuous learning, meaningful work, and collaboration. You will be empowered to deepen your technical expertise, explore innovative approaches, and take ownership of solutions that create measurable impact. We foster a culture that values curiosity, knowledge sharing, and professional development while providing opportunities to work alongside experienced AI, engineering, and business leaders. Our commitment to learning, collaboration, and career growth helps employees build skills that prepare them for future opportunities while making a difference today.
"In addition to the salary range, this role is also eligible for bonus or incentive opportunities."