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Director Machine Learning Biology Jobs in Texas (NOW HIRING)

Machine Learning Engineer

Austin, TX · On-site

$170K - $250K/yr

Your Job The ML Engineer will build physics-informed surrogate models on Azure Machine Learning ... Direct experience with industry-standard EM or physics simulation tools. * Geometric deep learning ...

New

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll ... Bring our research from concept to implementation, creating AI-driven applications with a direct ...

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Director Machine Learning Biology information

What is the difference between Director Machine Learning Biology vs Data Scientist Biology?

AspectDirector Machine Learning BiologyData Scientist Biology
Required CredentialsAdvanced degrees (PhD/Master's) in Biology, Computer Science, or related fields; experience in machine learningBachelor's or Master's in Data Science, Biology, or related fields; programming skills; some experience in machine learning
Work EnvironmentLeadership roles in R&D teams, strategic planning, overseeing projectsData analysis, model development, research, and reporting
Employer & Industry UsageBiotech, pharmaceutical companies, research institutionsBiotech, healthcare, research organizations, academia

The main difference is that the Director Machine Learning Biology focuses on leading teams and strategic initiatives in applying machine learning to biological data, while Data Scientist Biology primarily conducts data analysis and model development within biological research projects. The director role involves higher-level management and oversight, whereas the data scientist role is more hands-on with data and algorithms.

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Cities in Texas with the most Director Machine Learning Biology job openings:

Machine Learning Engineer - Strategic Data Solutions

Apple

Austin, TX • On-site

$113K - $136K/yr

Full-time

Re-posted 14 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that's constantly learning and having fun while solving tough business problems? We'd love to talk to you if you do!
At Apple, new ideas have a way of quickly becoming outstanding products, services, and customer experiences. Bring passion and dedication to your career, and there's no telling what you could accomplish! Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency. Our work touches all parts of Apple, from manufacturing to fulfillment to apps and services. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
As a SDS Machine Learning Engineer, you will work with teams across Apple, using data analysis and predictive modeling techniques to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers.
Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.
Description
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions
• Collaborate with technical partners to implement robust real-time and batch decisioning in production
• Create reporting and monitor decisioning quality to maintain operational and business metric health
• Investigate trends, assess threat impact, and respond with agile logic changes
• Communicate with stakeholders with varying technical backgrounds and business priorities about your work
• Share what you're learning about novel technologies and methods (in data science, machine learning, data engineering, and software engineering, etc) to improve your team's overall technical capabilities
Minimum Qualifications
Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, Political Science, Biology, etc) or Bachelor's degree with equivalent experience
At least 3 years of practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions
Practical experience with implementing data science-related applications in a programming language such as Python, Scala, or Java
Preferred Qualifications
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses
Ability to use a querying language such as SQL to extract insights from data
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions
Team-oriented skills and values to facilitate effective collaboration with business and technical partners

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976