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Salaried Political Data Science Jobs (NOW HIRING)

Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science Richmond, VA: $123,300 ...

New

... salary negotiation, promotion strategy, broader skill building, and support for those pursuing freelancing opportunities. Ideal candidates have hands-on experience in data science (as a data ...

Associate Director, Data Science

Cambridge, MA ยท Hybrid

$160K - $297K/yr

The salary for this position is expected to range between $160,300 and $297,700 per year. The final ... Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine ...

The salary for this position is expected to range between $194,600 and $361,400 per year. The final ... Science, Data Strategy, Electrical Transformer, Machine Learning (ML), Master Data Management ...

You will report into Director, Data Science on our Merchant Analytics team in our Analytics ... Base salary is localized according to an employee's work location. Ranges are market-dependent and ...

You will be working alongside our Data Science consultants and our clients on Data Science topics ... Salary + Annual Discretionary Bonus * Healthcare coverage that includes medical, dental, vision and ...

New

Director of Data Science

New York, NY ยท On-site

$225K - $250K/yr

At Brigit, our Data Science team has been dramatically scaling its impact. We're aiming to ... The actual base salary offered depends on a variety of factors, which may include as applicable ...

Showing results 41-60

Salaried Political Data Science information

What are the key skills and qualifications needed to thrive as a salaried political data scientist?

To thrive as a Salaried Political Data Scientist, you need strong analytical skills, proficiency in statistics, and a background in political science or related fields, often supported by an advanced degree. Familiarity with programming languages like Python or R, expertise in data visualization tools, and experience with databases and statistical modeling are typically required. Strong communication, problem-solving abilities, and the capacity to work under tight deadlines are crucial soft skills for this role. These competencies are essential for transforming complex data into actionable insights that inform political strategies and decision-making.

How much do political data scientists make?

Political data scientists typically earn between $70,000 and $120,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in data analysis, machine learning, and programming may earn higher salaries, especially in competitive political consulting or research organizations.

What is a salaried political data scientist?

A salaried political data scientist is a professional who uses statistical analysis, programming, and data modeling techniques to analyze political data for organizations, campaigns, or research institutions. Their work involves gathering and interpreting large datasets related to elections, public opinion, voter behavior, and policy impact. By uncovering patterns and insights, they help inform campaign strategies, policy decisions, and advocacy efforts. As salaried employees, they typically work full-time for political parties, consulting firms, non-profits, or governmental agencies.

What is the difference between Salaried Political Data Science vs Political Data Analyst?

AspectSalaried Political Data SciencePolitical Data Analyst
Required CredentialsBachelor's or higher in Data Science, Political Science, or related fields; often includes programming and statistical certificationsBachelor's degree in Political Science, Data Analysis, or related fields; some roles prefer certifications in data tools
Work EnvironmentResearch teams, campaign offices, government agencies; involves data modeling and predictive analyticsCampaign offices, think tanks, government agencies; focuses on data collection, reporting, and visualization
Employer & Industry UsagePolitical campaigns, government departments, consulting firmsPolitical campaigns, research organizations, policy institutes

Salaried Political Data Scientists typically engage in advanced data modeling, predictive analytics, and machine learning, requiring stronger technical skills. Political Data Analysts focus more on data collection, reporting, and visualization. Both roles are vital in political strategy but differ in technical depth and responsibilities.

What are some of the main challenges faced by political data scientists in a salaried position, and how can they be addressed?

One of the main challenges for salaried political data scientists is working with incomplete or rapidly changing datasets, especially during election cycles. Navigating data privacy regulations and ensuring ethical use of voter information can also pose difficulties. Collaboration with campaign strategists and communication teams is vital to translate complex analyses into actionable insights. Staying current with evolving political technologies and methodologies is key to success in this dynamic environment. Continuous learning and cross-functional teamwork can help address these challenges effectively.
What cities are hiring for Salaried Political Data Science jobs? Cities with the most Salaried Political Data Science job openings:
What are the most commonly searched types of Political Data Science jobs? The most popular types of Political Data Science jobs are:
What states have the most Salaried Political Data Science jobs? States with the most job openings for Salaried Political Data Science jobs include:

Sourcing - Director, Data Science: Data Science Tools

Liberty Information Technology Limited

Portsmouth, NH โ€ข On-site, Remote

Full-time

Re-posted 24 days ago


Job description

Description

The Data Science Infrastructureย organization within USRM is hiring a Senior Technical Professional, Data Scientistย to join the Data Science Toolsย team. This role will focus on improving the end-to-end modeling workflow for USRM Data Science by building internal tools, pipelines, and applications that streamline model development, evaluation, deployment, and iteration. The ideal candidate is highly technical, proactive, and motivated by building systems that help other data scientists work more efficiently.

**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. **

Responsibilities:

  • Design and build internal tools, pipelines, and applications that improve model development, evaluation, and deployment
  • Own strategy and roadmaps for improving data science workflows and tooling across USRM
  • Design, build, and maintain Python packages used across the organization
  • Evaluate and implement AI agent capabilities in tooling using approaches such as MCP, RAG, PydanticAI, LangChain, or related frameworks
  • Work with workflow and modeling tools such as Luigi, Airflow, Celery, MLflow, H2O, scikit-learn, Optuna, and LightGBM, as well as Python development tools such as Pydantic, FastAPI, uv, ruff, and pytest
  • Promote MLOps and AI agent best practices in collaboration with groups such as Enterprise Data & Data Science
  • Stay current on developments in open-source data science frameworks, MLOps, and agentic coding practices
  • Help shape the direction of the Tools team and contribute to a culture of ownership, collaboration, and continuous improvement

The ideal candidate will have:

  • Professional experience building and maintaining Python-based data science or Machine Learning tooling used by multiple end users or teams
  • Worked with any of the following in a professional setting: Git, Bash/shell scripting, uv, pre-commit, ruff, pytest, or Pydantic
  • Built, deployed, or maintained workflows or pipelines using any of the following: Airflow, Luigi, Celery, Databricks, or MLflow
  • Implemented or supported AI/LLM-based tooling using frameworks such as PydanticAI, LangChain, MCP, or RAG
  • Developed, reviewed, or maintained internal Python packages, APIs, or data science applications using tools such as FastAPI, Streamlit, Dash, NiceGUI, or Plotly
  • Applied agentic AI techniques in day-to-day development and incorporate AI capabilities directly into tools and applications where they create meaningful value for data scientists
Qualifications
  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
  • Advanced knowledge of predictive toolset; reflects as expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Ability to establish and build relationships within and outside the organization.
  • Ability to give effective training and presentations to management and other groups.
  • Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
  • Broad knowledge of business drivers and market context.
  • 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 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum ofย  6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum ofย  8 years of relevant experience.

Employees may apply for a new role after completing 12 months of employment in their current position.

Employees should review all role requirements and apply only for positions for which they are eligible. Hiring processes may vary by country, including differences in procedures, requirements, and timelines.ย  For country-specific details, please consult your local recruiting / HR team.

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://LMI.co/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
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  • San Francisco
Employment Type: FULL_TIME