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Predictive Modeling Jobs in Virginia (NOW HIRING)

Insurance Recruiting Solutions

$120K - $130K/yr

This role offers the opportunity to work on rate development, reserving, predictive modeling, and product strategy across both Personal and Commercial Lines. If you enjoy using data to influence ...

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Predictive Modeling information

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How much do predictive modeling jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for predictive modeling in Virginia is $58.21, according to ZipRecruiter salary data. Most workers in this role earn between $52.21 and $67.69 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Predictive Modeling position, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What is a Predictive Modeling job?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What is a predictive modeler?

A predictive modeler is a professional who develops statistical and machine learning models to forecast future outcomes based on historical data. They use tools like Python, R, or specialized software and often require knowledge of data analysis, statistics, and programming. Their work supports decision-making in various industries such as finance, marketing, and healthcare.

What jobs make $1,000,000 a year?

In predictive modeling, high-earning roles such as senior data scientists, machine learning engineers, and analytics directors can reach or exceed $1 million annually, especially in top tech companies or financial firms. These positions typically require advanced skills in statistical analysis, programming, and experience with big data tools, along with leadership responsibilities and often performance-based bonuses or equity.

Is 40 too late for data science?

Predictive modeling is a key role in data science, and age is not a barrier to entering the field. Many professionals transition into data science later in their careers by developing skills in programming, statistics, and tools like Python or R. Continuous learning and relevant experience are more important than age when pursuing a data science career.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What job makes $10,000 a month without a degree?

Predictive modeling roles, such as data scientists or machine learning engineers, can earn $10,000 or more per month with significant experience and expertise in statistical analysis, programming, and data tools. These jobs often require strong skills in Python, R, or SQL and may involve working in tech, finance, or consulting environments, but typically do not require a formal degree if skills are demonstrated through portfolios or certifications.
What are the most commonly searched types of Predictive Modeling jobs in Virginia? The most popular types of Predictive Modeling jobs in Virginia are:
What are popular job titles related to Predictive Modeling jobs in Virginia? For Predictive Modeling jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Predictive Modeling jobs in Virginia look for? The top searched job categories for Predictive Modeling jobs in Virginia are:
Predictive Modeling jobs near you

Data Scientist - Predictive Analytics

JANSON

Fairfax, VA • On-site

Full-time

Posted 4 days ago

Job description

Description:

The Data Scientist-Predictive Analytics will serve as a key member of JANSON’s the evolution of Army logistics by developing, implementing, and sustaining intelligent agentic systems and predictive models. Responsible for leveraging a strong academic foundation, the candidate will utilize platforms like Palantir Foundry to transform raw supply chain data and unstructured maintenance records into actionable foresight. This leader will serve as a key point of the transition from academic theory to operational execution, bridging the gap between traditional supervised learning and modern Generative AI (GenAI) to solve complex logistics challenges in real-time. The ideal candidate is all contractor personnel shall possess an active Secret security clearance or be eligible for and able to obtain and maintain a Secret clearance. Personnel without an active clearance may perform unclassified preparatory work while clearance processing is underway..
Key Responsibilities

  • Model Development: Assist the principal data scientist in developing and tuning predictive models (e.g., predicting equipment failure, estimating lead times, or optimizing inventory levels).
  • Data Engineering Support: Assist in data validation, feature engineering, and quality checks on large-scale Army datasets to ensure model integrity.
  • Palantir Integration: Progressively develop expert-level skills in Palantir Foundry to build, update, and reuse predictive dashboards.
  • Training & Documentation: Help develop and update training materials, job aids, and technical documentation for predictive tools to ensure institutional adoption.
  • Sustainment: Support the reuse and long-term maintenance of analytics products and sustainment artifacts.

Minimum Qualifications

  • Master’s Degree (or near completion) in Data Analytics or a related quantitative field.
  • 0–2 years of relevant experience (including significant graduate-level research, labs, teaching or internships).
  • Strong Foundational Knowledge: Deep understanding of supervised learning algorithms, statistical inference, and predictive modeling workflows.
  • Tooling: Demonstrated proficiency in Python-based data science stacks (e.g., Pandas, Scikit-learn) and SQL.
  • Documentation: High attention to detail in technical writing and version control.

Preferred Qualifications

  • Specialized Coursework: Graduate-level focus on Supply Chain Analytics, Stochastic Processes, or Predictive Modeling.
  • Platform Exposure: Prior experience with Palantir Foundry or similar enterprise data platforms.
  • Military Context: Familiarity with Army logistics data (e.g., GCSS-Army, FED LOG) or prior military/government exposure.
  • Visualization: Experience creating compelling data stories using Tableau, Power BI, or integrated platform tools.
Requirements:
  • Secret Security Clearance: Active or eligibility to obtain and maintain.
  • Technical Proficiency: Advanced academic or professional experience in Python and SQL.
  • Analytical Communication: Ability to translate complex statistical and probabilistic AI outputs into clear, actionable insights for military and civilian decision-makers.
  • Operational Agility: Willingness to travel up to 20% for in-person training and operational support.
  • Collaborative Mindset: Capable of working within multi-disciplinary teams to pair human expertise with machine intelligence.