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Temporary Machine Learning Scientist Jobs in Austin, TX

Cotality

Senior Machine Learning Scientist

Austin, TX · Hybrid

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with ...

IBS Software

Senior Machine Learning Scientist

Austin, TX · On-site

$90K - $123K/yr

We are currently seeking an experienced, dynamic, organized, self-starter to join as a Senior Machine Learning Scientist for our Consulting and Digital Transformation (CDx) line of business. Key ...

Avride

Machine Learning Engineer

Austin, TX

Nice to have * Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. * Experience developing ML algorithms for autonomous vehicles or robotics applications.

Avride

Machine Learning Engineer

Austin, TX · On-site

Nice to have * Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. * Experience developing ML algorithms for autonomous vehicles or robotics applications.

Varsity Tutors

Machine Learning Tutor

San Marcos, TX · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Preferred : • Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. • Experience developing ML algorithms for autonomous vehicles or robotics applications. • ...

Varsity Tutors

Machine Learning Tutor

Round Rock, TX · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Austin, TX · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Temporary Machine Learning Scientist information

What is the difference between Temporary Machine Learning Scientist vs Data Scientist?

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

What are the key skills and qualifications needed to thrive as a temporary machine learning scientist, and why are they important?

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.
What are the most commonly searched types of Machine Learning Scientist jobs in Austin, TX? The most popular types of Machine Learning Scientist jobs in Austin, TX are:
What are popular job titles related to Temporary Machine Learning Scientist jobs in Austin, TX? For Temporary Machine Learning Scientist jobs in Austin, TX, the most frequently searched job titles are:
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Temporary Machine Learning Scientist jobs near you

Senior Machine Learning Scientist

Cotality

Austin, TX • Hybrid

Full-time

Medical, Life, Retirement, PTO

Posted 4 days ago

Job description

At Cotality, we are driven by a single mission-to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society.

Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry.

Job Description:

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with strategic thinking to drive innovation and solve challenging business problems through data-driven approaches.

Job Responsibilities:

  • Model Development: Design, develop, and implement sophisticated machine learning models and algorithms to address complex business challenges.

  • Research Leadership: Lead research initiatives to explore cutting-edge machine learning techniques and methodologies.

  • Data Analysis: Analyze large, diverse data sets to identify patterns, trends, and insights that drive business value.

  • Cross-Functional Collaboration: Partner with cross-functional teams to understand business requirements and translate them into actionable technical solutions.

  • Pipeline Engineering: Develop and optimize data processing pipelines for data preprocessing, feature engineering, model training, and evaluation.

  • Data Integration: Evaluate and integrate new data sources to continuously enhance model performance and business insights.

  • Performance Monitoring: Continuously monitor production model performance and implement technical improvements as needed.

  • Stakeholder Communication: Present complex findings, insights, and recommendations clearly to both technical and non-technical stakeholders.

  • Mentorship: Mentor junior data scientists and machine learning engineers, providing technical guidance and driving knowledge sharing across the team.

  • Documentation: Create and maintain rigorous documentation for models, methodologies, and technical processes.

Job Qualifications:

  • Education: Advanced degree (Master's or PhD) in Computer Science, Statistics, Mathematics, a related quantitative field or equivalent work experience.

  • Experience: 3+ years of relevant industry work experience.

  • Programming & Frameworks: Strong programming skills in Python and extensive experience with machine learning frameworks and libraries (e.g., PyTorch, scikit-learn).

  • Production ML: Demonstrated expertise in developing, deploying, and maintaining machine learning models in production environments.

  • Cloud & Big Data: Proven experience working with big data technologies and major cloud computing platforms (GCP, AWS, Azure).

  • Statistical Proficiency: Strong foundational understanding of statistical analysis, experimental design, and hypothesis testing.

  • Data Storytelling: Exceptional verbal, written, and listening skills with a demonstrated ability to communicate complex data insights clearly to diverse audiences.

  • Navigating Ambiguity: Excellent problem-solving skills with a proven track record of delivering results while working with ambiguous business requirements.

  • Distributed Computing: Hands-on experience with distributed computing frameworks (e.g., Apache Spark, Ray, Dask, or Hadoop) to scale machine learning workloads and process massive datasets.

#LI-Hybrid

Annual Pay Range:

111,900 - 130,000 USD

Application Window:

This opportunity is expected to remain posted through the date identified below, subject to business needs.

Thrive with Cotality

At Cotality, we offer more than just a job, we provide a benefits experience designed to support your whole self. From a flexible working model to competitive time off and standout health coverage with meaningful perks and growth opportunities, our package is built to help you thrive at work and in life.

Highlights, depending on role classification, include:

  • Time off: Generous PTO and 11 paid holidays, plus well-being and volunteer time off.

  • Family Support: Up to 16 weeks of fully paid parental leave and a baby stipend.

  • Health: Multiple medical plan options with mental health and wellness support offerings.

  • Retirement: 401(k) with company match and vesting after one year.

  • Financial Perks: $400 annual well-being stipend and tuition assistance up to $5,250.

  • Extras: Recognition Rewards, Referral bonuses, exclusive discounts and more!

Cotality is an Equal Opportunityemployer committed to attracting and retaining thebest-qualified people available, without regard torace, color, religion, national origin, gender, sexualorientation, gender identity, age, disability or statusas a veteran of the Armed Forces, or any other basisprotected by federal, state or local law. Cotalitymaintains a Drug-Free Workplace.

Cotality is fully committed to a work environment that embraces everyone's uniquecontributions, experiences and values. We offer anempowered work environment that encouragescreativity, initiative and professional growth andprovides a competitive salary and benefits package. We are better together when we support and recognize our differences.

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