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Data Science Assistant Jobs in Forney, TX (NOW HIRING)

You should not apply for this role if you will require Toyota to assist with immigration support or sponsorship now or in the future. Who we're looking for Toyota's OneTech Data Science and Machine ...

Independently work on data science projects and deliver innovative technical solutions to solve ... Assist engagement with key business stakeholders in discussion on business strategies and ...

You should not apply for this role if you will require Toyota to assist with immigration support or ... This role is ideal for someone who will thrive working at the intersection of computational science ...

Agentic AI, AI & Data Science Engineer

Dallas, TX · On-site

$113K - $136K/yr

Work you'll do As an AI and Data Science Engineer III on the AI & Data team, you will be ... Amazon Q Business & Q Developer (enterprise AI assistant and code generation capabilities); Cognito ...

You should not apply for this role if you will require Toyota to assist with immigration support or ... This role applies mathematical optimization, operations research, data science, and cloud-based ...

Responsibilities * Assist with and execute data science projects, working with product, engineering and/or customer service teams to identify requirements, perform analysis, and present results and ...

Key Responsibilities: * Assist in the scoping, execution, and completion of projects that align ... Bachelor's degree in Mathematics, Science, Engineering, Computer Science, Data Science, Statistics ...

Key Responsibilities: * Assist in the scoping, execution, and completion of projects that align ... Bachelor's degree in Mathematics, Science, Engineering, Computer Science, Data Science, Statistics ...

These efforts will encompass exploring AI solutions that serve as intelligent work assistants ... Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial ...

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a Data Science Assistant, and why are they important?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data Science Assistants and other data science roles do not have strict age limits; many professionals start or transition into data science later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned at any age through online courses, certifications, and practical experience.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or tasks to improve model performance efficiently.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What do data assistants do?

Data Science Assistants support data analysis by collecting, cleaning, and organizing data sets. They often use tools like Excel, SQL, or Python to prepare data for modeling and reporting, assisting data scientists and analysts in project workflows.

Can I get a data scientist job with no experience?

Entry-level data science assistant roles often do not require prior experience, but candidates typically need a strong foundation in programming (such as Python or R), statistics, and data analysis. Gaining relevant skills through online courses, certifications, or personal projects can improve chances of securing such positions.
What are the most commonly searched types of Data Science jobs in Forney, TX? The most popular types of Data Science jobs in Forney, TX are:
What cities near Forney, TX are hiring for Data Science Assistant jobs? Cities near Forney, TX with the most Data Science Assistant job openings:
Assistant Director, Data Science: Claims & Service

Assistant Director, Data Science: Claims & Service

Liberty Mutual

Plano, TX • On-site, Remote

$109K - $131K/yr

Full-time

Posted 12 days ago


Liberty Mutual rating

9.0

Company rating: 9.0 out of 10

Based on 145 frontline employees who took The Breakroom Quiz

36th of 298 rated insurance


Job description

Description

At Liberty Mutual, the Insights & Solutions group uses data, analytics, and technology to deliver innovative solutions that drive our US Retail Markets business forward. Within it, the Claims Data Science team focuses on developing sophisticated AI/ML driven solutions to help create the most accurate, caring, and efficient claims organization in the insurance industry.

Claims Data Science is bursting with opportunity. Recent advances in Large Language Models, Computer Vision, and other technologies bring many previously impracticable business challenges into the realm of possibility for data scientists. Claims Data Science can be a key competitive advantage for Liberty Mutual in the years to come; help us build that competitive advantage!

**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel. **

As an Assistant Director you will: 

Apply knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions.

Lead end-to-end development of new predictive models for high-impact business outcomes (e.g., improving claims handling efficiency): frame and test hypotheses, design statistically rigorous experiments, assemble/label training data, engineer features, and train/validate models.

Build state-of-the-art ML systems that leverage structured data, unstructured text, and generative AI.

Select and implement appropriate algorithms and evaluation methods to deliver measurable accuracy and business value.

Follow ML Ops best practices to create organized code repos, production-quality code, and reproducible results.

Stay up-to-date with the latest advancements in data science and machine learning, and apply them to solving complex problems in the insurance claims domain.

Provide technical mentorship and guidance to junior data scientists.

Responsible for larger components of projects of moderate to high complexity.

Communicate findings through technical presentations, reports, and recommendations to both technical and non-technical stakeholders.

Participate in cross-functional working groups and contribute to the broader data science community to promote best practices.

Preferred skills and experience:

Broad conceptual understanding and practical knowledge of the end-to-end data science lifecycle.

Exceptional hands-on data science technical skills (e.g. SQL, Python, and Statistical Inference).

Experience collaborating with non-technical stakeholders to understand which problems need solving, design solutions, and bring them to market.

Experience working with complex Type II data to assemble training datasets to appropriately model operational processes.

Proficiency in Python and MLOps practices, with experience in version control (Git), code review, collaborative development workflows (e.g., GitHub/GitLab), and model versioning/experiment tracking (e.g., MLflow).

Additional skills and experiences that are nice to have:

Knowledge of claims handling processes and experience working with claims data.

Experience developing LLM-based solutions for production use cases.

Practical experience with cloud platforms like AWS (preferably), Google Cloud, or Azure.

Familiarity with data pipeline and workflow management tools like Airflow, among others.

Qualifications
  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
  • Expert knowledge of predictive toolset; reflects as expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU.
  • Ability to give effective training and presentations to peers, management and less senior business leaders.
  • Ability to use results of analysis to persuade team or department management to a particular course of action.
  • Has a value driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 2 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 4 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of 5+ years of relevant experience.
About Us

Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve. We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://www.libertymutualgroup.com/about-lm/careers/benefitsLiberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.Fair Chance Notices

  • California
  • Los Angeles Incorporated
  • Los Angeles Unincorporated
  • Philadelphia
  • San Francisco
Employment Type: FULL_TIME

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About Liberty Mutual

Sourced by ZipRecruiter

Since 1912, we've grown into the fifth largest global property and casualty insurer based on 2022 gross written premium. We also rank 86 on the Fortune 100 list of largest corporations in the US based on 2022 revenue. ​At Liberty Mutual Insurance we work hard every day to support our customers and our people, so they can protect their families, build their businesses and invest in their futures. We are headquartered in Boston, but our people, our customers and our reach span the globe. So to better serve our global customers and employees, we are organized into three business units.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

Boston, MA, US

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