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Mathematical Optimization Remote Jobs in Texas (NOW HIRING)

Adidev Technologies Inc

DATA SCIENTIST

Austin, TX · Remote

Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.) * Experience ... Remote Support * Guaranteed Regular Salary Reviews * Job Type: W2 or Contract 1099 (full-time - 40 ...

Arva Intelligence

Modeling Scientist

Houston, TX · On-site +1

$100K - $160K/yr

Remote Base Salary Range : $100k - $160k base salary The Modeling Scientist is responsible for ... Contribute to the design of model evaluation and optimization workflows Scientific Communication ...

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Mathematical Optimization Remote information

What are some common challenges faced by professionals in remote mathematical optimization roles, and how can they be addressed?

Remote mathematical optimization professionals often encounter challenges such as limited real-time collaboration with team members, managing complex problem-solving tasks independently, and ensuring effective communication of technical findings to non-technical stakeholders. To address these challenges, it's helpful to establish regular virtual meetings, use collaborative tools for sharing code and results, and develop clear documentation. Additionally, proactively seeking feedback and staying engaged with the broader team can help maintain alignment and foster innovation.

What is a Mathematical Optimization Remote job?

A Mathematical Optimization Remote job involves using mathematical techniques and algorithms to solve optimization problems, such as maximizing efficiency or minimizing costs, while working from a remote location. Professionals in this field apply optimization theory, modeling, and computational methods to real-world problems in industries like logistics, finance, engineering, and data science. Remote roles allow for flexibility, enabling collaboration with teams and clients online while leveraging specialized software and programming languages such as Python, MATLAB, or R.

Can dyslexia affect math?

Dyslexia primarily impacts reading and language processing, but it can also affect math skills, especially in areas involving word problems, sequencing, and symbol recognition. In a mathematical optimization role, strong analytical and technical skills are essential, and individuals with dyslexia can succeed by utilizing tools like visual aids, software, and accommodations to support their learning and performance.

Why did Finn stop saying mathematical?

There is no known connection between the job of Mathematical Optimization Remote and someone named Finn stopping to say 'mathematical.' If this refers to a specific individual or context, it is unrelated to the job role, which involves applying mathematical techniques to optimize processes remotely. The phrase may be a personal or humorous reference rather than a professional or industry-related change.

Is Royal Holloway good for maths?

Royal Holloway offers a reputable mathematics program with strong research and teaching quality, making it a solid choice for students interested in mathematics. For those pursuing a mathematical optimization remote role, a solid foundation in advanced mathematics and familiarity with relevant tools like programming languages or optimization software are beneficial. The university's curriculum can support skills needed for such roles.

What is the difference between Mathematical Optimization Remote vs Data Analyst Remote?

AspectMathematical Optimization RemoteData Analyst Remote
Required CredentialsDegree in Mathematics, Operations Research, or related field; proficiency in optimization softwareDegree in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentRemote, often collaborative with teams on complex modeling projectsRemote, focused on data collection, visualization, and reporting
Industry UsageFinance, logistics, supply chain, tech companiesMarketing, finance, healthcare, tech companies
Common Search/ComparisonYesNo

Mathematical Optimization Remote specialists focus on developing algorithms to optimize processes and decision-making, often requiring advanced mathematical skills. Data Analysts Remote interpret data to provide insights, using statistical tools. While both roles are remote and involve data, they differ in technical focus and industry applications.

What are the key skills and qualifications needed to thrive as a Mathematical Optimization Specialist working remotely, and why are they important?

To thrive as a Mathematical Optimization Specialist in a remote setting, you need a strong background in mathematics, operations research, or computer science, often supported by an advanced degree. Proficiency with optimization software (such as Gurobi, CPLEX, or MATLAB), programming languages like Python or R, and familiarity with cloud-based collaboration tools is typically required. Excellent problem-solving abilities, self-motivation, and clear communication skills help you stand out when collaborating with distributed teams and stakeholders. These skills and qualities are crucial for efficiently developing, implementing, and explaining optimization solutions in a remote work environment.
What are the most commonly searched types of Mathematical Optimization jobs in Texas? The most popular types of Mathematical Optimization jobs in Texas are:
What are popular job titles related to Mathematical Optimization Remote jobs in Texas? For Mathematical Optimization Remote jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Mathematical Optimization Remote jobs in Texas look for? The top searched job categories for Mathematical Optimization Remote jobs in Texas are:
What cities in Texas are hiring for Mathematical Optimization Remote jobs? Cities in Texas with the most Mathematical Optimization Remote job openings:
Mathematical Optimization Remote jobs near you

R&D Data Scientist: Mathematical Modeling and Optimization

Liftlab Analytics, Inc.

Austin, TX • Remote

Full-time

Posted 4 days ago

Job description

(Fully-remote US position)
About LiftLab

Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance.

Job responsibilities

  • Develop new algorithm-based features of LiftLab's marketing measurement and optimization platform

  • Performs diagnostics and root-cause analysis and provide fixes

  • Works with Data Science and Engineering to implement these features into LiftLabs product and workflow

Course work/experience:

  • Data manipulation

    • SQL

    • Operating on big datasets in Python

    • Data visualization

  • Mathematical optimization

    • Linear optimization concepts

    • Nonlinear continuous optimization

    • Linear algebra

  • Mathematical modeling

    • Using parametrized systems of equations to represent real-world systems

  • Statistics

    • Multivariate regression

    • Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters

    • Bayesian concepts

    • Hypotheses testing

Education requirements

Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience

Skills/Aptitude

  • Engineering and detective mindset

    • Both to diagnose data and existing algorithms and to develop new analytics functionality

  • Pragmatic approach to real-world problems

  • Focus on problem solving over applying specific models

  • Willingness to make approximations and assumptions rather than find "the" optimal solution

  • Ability to combine multiple techniques and models to solve end-to end-problems

  • Communication and collaboration skill

  • Ability to convert non-technical requests into project specifications

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