Data Scientist

StriveWorks, Inc
Austin, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 230K

Job location

Remote
Austin, United States of America

Tech stack

Java
Artificial Intelligence
Amazon Web Services (AWS)
Azure
C++
Cloud Computing
Continuous Integration
ETL
DevOps
Python
Machine Learning
TensorFlow
Software Systems
SONAR (Symantec)
Rust
Google Cloud Platform
PyTorch
DevOps Tools - Open-source
GIT
Scikit Learn
Kubernetes
Information Technology
Data Pipelines
Docker
Programming Languages

Job description

As a Senior Data Scientist at Striveworks, you'll be challenged-and trusted-on day one to be a core contributor to the projects, products, and direction of the company. You will be a key Striveworks representative and technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will work as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers to transform machine learning models into functional products.

You're right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You're outcome driven and are passionate about applying both software and data science to solve real-world problems. You know that being customer focused, rigorous in approach, clear in communication, and able to identify repeatable value opportunities are all critical to success. You are able to sense the needs of the customer, identify evolving demands, and then synthesize that feedback into actionable suggestions for Striveworks' product teams.

Your day-to-day will include:

  • Working with customers, engineers, and other stakeholders to define clear requirements that solve customers' problems and leverage the capabilities of our AIOps platform
  • Developing and validating machine learning models and custom analytic algorithms that are applied to image, video, text, geospatial, time series, and structured data
  • Orchestrating and automating complex data and analytic pipelines
  • Implementing AI-based software solutions for cloud and edge environments
  • Conducting mission-critical field work and interfacing with customers and other stakeholders

This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 25% of the time.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust.

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Requirements

  • Bachelor's degree in computer science, machine learning, mathematics, or a related discipline and 6+ years of relevant experience
  • Expertise in machine learning, data science, and their application to image and video data, as well as experience deploying those capabilities to production environments
  • Expertise in implementing and analyzing algorithms and data structures
  • Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
  • Exposure to DevOps tooling and best practices (e.g., Git, Docker, Kubernetes, CI/CD)
  • Active Secret (or above) US security clearance
  • Due to the nature of this role, candidates must have US citizenship, * Graduate degree in computer science, machine learning, mathematics, or a related discipline
  • Experience processing a variety of unstructured data types (e.g., imagery, full motion video, text, acoustic, sonar, RF, geospatial, graphs, or telemetry signals)
  • Experience building AI agents and agentic workflows
  • Experience implementing ETL pipelines, data pipelines, and/or workflow automation
  • Experience developing solutions in a compiled programming language (Go, Rust, C++, Java, etc.)
  • Experience building full-stack applications (back end, front end, REST) or solutions targeted for cloud infrastructure (AWS, Azure, GCP) and/or Kubernetes (K8s)
  • Experience leading a small team
  • Experience delivering technology solutions in secure government environments
  • Experience working with federal, state, and/or local government customers

Benefits & conditions

The anticipated base pay range for this position is $185,000-$230,000/year. Striveworks' total compensation package includes a competitive base salary, equity grants, and cash bonuses., * Medical/dental/vision insurance

  • Voluntary life, long-term disability, accident, and hospital indemnity insurance
  • HSA and FSA (including dependent care FSA) plans
  • 401(k) plan
  • Unlimited PTO
  • Paid parental leave

About the company

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective. With Striveworks, organizations aren't just deploying AI-they're building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they're deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs-and enabling confident, data-driven decision-making in dynamic environments.

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