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Experienced Data Scientist Jobs (NOW HIRING)

MedReview

Data Scientist

Austin, TX · On-site

MedReview is looking for a talented and experienced Data Scientist to join our dynamic team. As a part of our team, you will leverage your analytical skills and expertise in machine learning to ...

Innotech

Data Scientist

Houston, TX

$12K - $78K/yr

We're seeking an experienced data scientist to deliver insights on a daily basis. The ideal candidate will have mathematical and statistical expertise, along with natural curiosity and a creative ...

MedReview

Data Scientist

Austin, TX · On-site

MedReview is looking for a talented and experienced Data Scientist to join our dynamic team. As a part of our team, you will leverage your analytical skills and expertise in machine learning to ...

Apple

Data Scientist

Cupertino, CA · On-site

Description We are looking for a talented, experienced Data Scientist to join our cross-functional team, focusing on evaluating routing service quality, ensuring its accuracy and reliability, and ...

PROPRIUS

Data Scientist

Sunnyvale, CA

$130K - $160K/yr

Yes Industry: eCommerce Are you an experienced Data Scientist with 2+ years' experience who likes solving complex problems? Do you want to work for a rapidly-expanding technology division within a ...

Waypoint Human Capital

Data Scientist

San Antonio, TX · On-site

Active TS/SCI Waypoint's client is seeking an experienced Data Scientist to support the Joint Electromagnetic Warfare Center (JEWC) by providing advanced data analytics, machine learning, and ...

MORSE Corp

Data Scientist

Cambridge, MA · On-site

They are searching for an experienced Data Scientist to perform data analysis and algorithm development in various fields to support national security customers. Responsibilities : • Perform data ...

Figma

Data Scientist

They are looking for an experienced Data Scientist to join their data team, collaborating across functions to drive impactful data projects and guide strategic decision-making. Responsibilities : • ...

Figma

Data Scientist

They are looking for an experienced Data Scientist to join their growing data team, where the role involves collaborating across teams to define metrics, build analytical frameworks, and drive data ...

Figma

Data Scientist

They are looking for an experienced Data Scientist to join their growing data team, where the role involves collaborating across teams to drive impact through data-driven insights and solutions.

VTG

Data Scientist

Mclean, VA

Overview VTG is seeking a talented and experienced Data Scientist to join our dynamic and innovative team in Herndon, VA/Chantilly, VA. What will you do? * Collect, clean, and analyze large, complex ...

Two Six Technologies

Data Scientist

Arlington, VA · On-site

We're looking for an experienced Data Scientist or Senior Data Scientist to join one of our cross-functional product development teams here at Two Six Technologies. Our teams are building ...

VTG

Data Scientist with Security Clearance

Chantilly, VA · On-site

$165K - $210K/yr

The impact an experienced data scientist can have on an organization is immense including automating manual processes, predicting future trends, and detecting anomalies. Data Scientist experience ...

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How much do experienced data scientist jobs pay per year?

As of Jul 14, 2026, the average yearly pay for experienced data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

An experienced data scientist can start or transition into the field at age 40, as skills in programming, statistics, and machine learning are more important than age. Many professionals successfully switch careers or advance in data science later in life by gaining relevant certifications and building a strong portfolio.

What are some typical challenges an experienced data scientist faces when working on cross-functional teams?

Experienced data scientists often collaborate with cross-functional teams, such as product managers, engineers, and business analysts. A common challenge in this environment is effectively communicating complex analytical findings in a way that is actionable for non-technical stakeholders. Additionally, aligning data science objectives with broader business goals and navigating differing priorities can require strong negotiation and project management skills. Overcoming these challenges is key to ensuring that data-driven insights are not only understood but also implemented to drive impact.

What are experienced data scientists?

Experienced data scientists are professionals who have a strong background in data analysis, statistical modeling, and machine learning, typically with several years of industry experience. They use advanced analytical techniques to extract insights from complex data sets, helping organizations make data-driven decisions. In addition to technical skills, they often possess domain expertise, strong problem-solving abilities, and experience in communicating their findings to both technical and non-technical stakeholders. Their work may involve designing experiments, building predictive models, and deploying machine learning solutions in production environments.

What is the 80 20 rule in data science?

The 80/20 rule in data science, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this rule to prioritize data cleaning, feature selection, and model tuning to focus on the most impactful variables and improve efficiency.

How much does an experienced data scientist make?

An experienced data scientist typically earns between $100,000 and $150,000 annually, with salaries increasing based on industry, location, and expertise in tools like Python or R. Senior roles or those with specialized skills can exceed $170,000 per year.

What are the key skills and qualifications needed to thrive as an Experienced Data Scientist, and why are they important?

To thrive as an Experienced Data Scientist, you need advanced statistical analysis, machine learning expertise, strong programming skills (often in Python or R), and a relevant degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL, and cloud platforms, as well as certifications in data science or analytics, are commonly expected. Outstanding problem-solving, communication skills, and business acumen help you translate complex data insights into actionable strategies. These skills are essential for delivering impactful solutions and driving data-informed decision-making within organizations.

What is the difference between Experienced Data Scientist vs Data Analyst?

AspectExperienced Data ScientistData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fields; often certifications in machine learning or data analysisBachelor's degree in Statistics, Mathematics, or related fields; certifications are optional
Work EnvironmentDevelops models, algorithms, and predictive analytics; works on complex data projectsPrepares reports, visualizations, and performs data cleaning and basic analysis
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceRetail, marketing, finance, and business intelligence

In summary, an Experienced Data Scientist typically handles advanced analytics, machine learning, and predictive modeling, requiring more technical skills and higher education. Data Analysts focus on data cleaning, reporting, and visualization, often with less emphasis on complex modeling. Both roles are essential but differ in scope and technical depth.

Is a data scientist job still in demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and the field continues to grow as organizations seek to leverage big data for competitive advantage.
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Experienced Data Scientist jobs near you
Data Scientist

Data Scientist

Avani Technology Solutions, Inc.

San Francisco, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Role: Data Scientist
Location: San Francisco, CA
Duration: 6+ Months
Team Overview:
The Digital Catalyst Team is a new enterprise team that is responsible for working collaboratively with the lines of business to implement consumer grade mobile and analytical solutions across various user groups (e.g., field users, office workers, etc.). This includes, but is not limited to:
  • Deploying best-in-class / rapid delivery capability for mobile solutions.
  • Simplifying, improving, and standardizing business work management processes for mobile needs.
  • Delivering high value analytics across all Lines of Businesses.
  • Rapid delivery of web applications.

Digital Catalyst consists of a staff of highly skilled professionals working together to produce mobile solutions following an agile methodology and design thinking. We are a "start-up" department within IT and building driven and creative mobile development team. We take the time to understand our partners' needs and translate those into solutions that delight our users. Our goal is to deliver products with intuitive user experience that will improve employees' and customer's safety, productivity and overall well-being.
Position Summary:
We are seeking an experienced Data Scientist in the Digital Catalyst Team who will provide strong execution and delivery of data science. Working as a part of the product team, this Data Scientist will translate business needs into advanced analytics and machine learning models. The successful candidate will be responsible for model selection and identification of appropriate training data sets; building, training, and evaluating models; and delivering results to the business on a regular cadence. This role is part of a fully Agile Scrum team, so the data scientist will work alongside a product owner, technical lead, and team of developers and data engineers to support delivery of high-value analytics and software products.
Position Responsibilities:
  • Leads development of high complexity models and training sets
  • Provides hands-on execution and implementation of data science models
  • Translates business analysis needs into well-defined data science problems, and selecting appropriate models and algorithms and communicates model evaluation and implications of results back to stakeholders
  • Recognizes and prioritizes the most important work related to data science models to achieve highest operational impact for analytics in the business
  • Balances tradeoffs among analytics value, model development methods and design and technologies used to implement data science models with a bias toward action
  • Performs collaborative work on data science problems and mentor junior data scientists
  • Creates shared process models, business objects, activity diagrams and process documentation to effectively articulate multiple views of the business solutions that support technical architecture.
  • Manages development of quantitative models and tools.
  • Collaborates with leaders, other LOBs, and business partners to work on issues, projects or activities.
  • Develops new or revises complex models to predict business demand trends, and volume and expenditures forecasts capacity analysis, and various other metrics to identify potential opportunities.
  • Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
  • Partners with leaders to drive high performance in their lines of business.
  • Develop deep understanding of business drivers and financial levers to provide strategic decision support.
  • Oversees resolution of complex projects and programs.
  • Develops and maintains up-to-date detailed project schedules and work plans.
  • Performs analysis on complex data models requiring customized reports and data and presents recommendations.

Minimum Education/Skills:
  • Bachelor's Degree in Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience
  • Job-related experience, 8 years, OR Master's Degree and job-related experience, 6 years, OR Doctorate Degree and job-related experience, 3 years
  • Experience in data modeling, 5yrs

Desired Education / Skills:
  • PhD in engineering or a related field (computer science, natural sciences, mathematics)
  • Experience with Python, R, Scala, SQL
  • Experience developing solutions with Pandas/Scikit-learn, Spark or comparable technologies
  • Experience data science notebooks (Jupyter, Zeppelin or other)
  • Experience with AWS, Azure, cloud computing technologies
  • Scrum team experience
  • Energy industry experience
  • Experience designing efficient data science workflows and database architecture for data science purposes
  • Experience with forecasting, Bayesian networks, and graph analytics
  • Strong statistics experience
  • Experience with software development methodologies and software engineering principles
  • Knowledge of program management theories, concepts, methods, best practices, and techniques as needed to perform at the job level
  • Knowledge of relevant programming languages - for example Visual Basic, Ladder Logic,
  • Programmable Logic Controller, C, SharePoint, HTML, Java, Adobe - as needed to perform at the job level
  • Competency in knowing the most effective and efficient processes to get things done, with a focus on continuous improvement
  • Knowledge of principles, techniques, and procedures used for production and design of technology based equipment and systems as needed to perform at the job level
  • Knowledge of statistical theories, concepts, methods, best practices, and analyses as needed to perform at the job level
  • Ability to develop reports, models, and simulations as needed to perform at the job level
  • Competency in developing and delivering multi-mode communications that convey a clear
  • understanding of the unique needs of different audiences
  • Knowledge of data model design philosophies and methodologies for data warehouse and OLTP systems

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