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Remote Data Analyst Python Jobs in Washington, DC

We are hiring a Business Data Analyst for an exciting remote opportunity. and Responsibilities Provides comprehensive, matrixed analytical support across all portfolio programs by delivering in-depth ...

Junior Data Analyst

Arlington, VA ยท On-site +1

$50K - $75K/yr

TSTC is seeking a full-time Junior Data Analyst to provide research services for one of TSTC ... Flexible Work Options - Remote work allowed, flexible schedules, and telework opportunities ...

Junior Data Analyst

Arlington, VA ยท On-site +1

$50K - $75K/yr

TSTC is seeking a full-time Junior Data Analyst to provide research services for one of TSTC ... Flexible Work Options - Remote work allowed, flexible schedules, and telework opportunities ...

Sr. Data Analyst (part-time, hybrid)

Arlington, VA ยท On-site +1

$98K - $124K/yr

Tier One Technologies is looking for a Data Analyst for our direct US Government client. * This ... Python, R, and Java Scripts). * 3+ years of experience working with Microsoft Power Platform ...

Senior Consultant Data Analyst

Arlington, VA ยท On-site +1

$98K - $124K/yr

Our analysts are team-oriented, collaborative, and focus on delivering value in everything we do ... Transform and cleanse data using tools such as R, SQL, or Python. * Interpret, understand, and ...

Data Analyst (Oracle HCM Cloud) 100% remote Pay Rate: Open to Both C2C and W2 options Position Type: Multiyear Contract We are seeking an experienced contractor to support advanced data development ...

Data Analyst (Oracle HCM Cloud) 100% remote Pay Rate: Open to Both C2C and W2 options Position Type: Multiyear Contract We are seeking an experienced contractor to support advanced data development ...

Data Analyst (Oracle HCM Cloud) 100% remote Pay Rate: Open to Both C2C and W2 options Position Type: Multiyear Contract We are seeking an experienced contractor to support advanced data development ...

Data Analyst (Oracle HCM Cloud) 100% remote Pay Rate: Open to Both C2C and W2 options Position Type: Multiyear Contract We are seeking an experienced contractor to support advanced data development ...

Data Analyst (Oracle HCM Cloud) 100% remote Pay Rate: Open to Both C2C and W2 options Position Type: Multiyear Contract We are seeking an experienced contractor to support advanced data development ...

Data Analyst (Oracle HCM Cloud) 100% remote Pay Rate: Open to Both C2C and W2 options Position Type: Multiyear Contract We are seeking an experienced contractor to support advanced data development ...

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Remote Data Analyst Python information

See Washington, DC salary details

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How much do remote data analyst python jobs pay per year?

As of Jul 10, 2026, the average yearly pay for remote data analyst python in Washington, DC is $93,598.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,800.00 and $109,900.00 per year, depending on experience, location, and employer.

What is the salary of Python 2 years experience?

A remote data analyst with two years of Python experience typically earns between $60,000 and $80,000 annually, depending on location, industry, and skill level. Proficiency in data manipulation, visualization, and relevant tools like Pandas or SQL can influence salary ranges.

Can I be a data analyst with just Python?

A data analyst role typically requires knowledge of multiple tools and skills, including SQL, Excel, and data visualization software, in addition to Python. While Python is a valuable skill for data analysis, relying solely on it may limit your ability to perform all necessary tasks effectively. Developing a broader skill set can improve job prospects and performance in data analyst positions.

How do Remote Data Analyst Python roles typically coordinate with other team members, given the virtual work environment?

Remote Data Analyst Python roles usually involve frequent collaboration with cross-functional teams such as product managers, data engineers, and business analysts through virtual platforms. Communication is commonly facilitated via video meetings, chat tools, and shared project management software to ensure alignment on data requirements and project goals. While working remotely requires strong self-motivation, most organizations support analysts with regular check-ins and clear documentation practices. This collaborative structure helps maintain productivity and ensures that data insights are effectively integrated into decision-making processes.

Will AI replace data analysts?

AI tools can automate routine data processing and analysis tasks, but data analysts are essential for interpreting complex insights, making strategic decisions, and ensuring data quality. The role of a remote data analyst with skills in Python and data visualization remains valuable, as AI complements human expertise rather than replacing it entirely.

What is a Remote Data Analyst Python?

A Remote Data Analyst Python is a data professional who works primarily from a remote location, using Python programming to collect, analyze, and interpret data. Their responsibilities include cleaning and processing data, creating data visualizations, and building models to support business decisions. They often collaborate with teams virtually and use Python libraries such as pandas, NumPy, and matplotlib to handle complex data tasks. This role is ideal for those who have strong analytical skills, proficiency in Python, and the ability to work independently in a remote environment.

Is 40 too late for data science?

Age is not a barrier to becoming a data analyst or transitioning into data science; many professionals start or switch careers later in life. Success depends on acquiring relevant skills such as Python, SQL, and machine learning, along with practical experience and certifications. Employers value diverse backgrounds and experience, making 40 a reasonable age to pursue a data science career if you build your skills and portfolio.

What are the key skills and qualifications needed to thrive as a Remote Data Analyst (Python), and why are they important?

To thrive as a Remote Data Analyst (Python), you need strong analytical skills, proficiency in Python programming, a solid grasp of statistics, and typically a degree in a quantitative field. Expertise with data analysis libraries (such as pandas and numpy), familiarity with data visualization tools (like matplotlib or Tableau), and experience with SQL databases are highly valued. Excellent problem-solving, communication skills, and self-motivation are crucial for collaborating remotely and delivering actionable insights. These skills enable you to efficiently interpret complex data, work independently, and provide valuable business recommendations from a remote setting.

What is the difference between Remote Data Analyst Python vs Remote Data Analyst R?

AspectRemote Data Analyst PythonRemote Data Analyst R
Required SkillsPython, SQL, data visualization, statistical analysisR, SQL, data visualization, statistical analysis
Work EnvironmentRemote, tech companies, finance, healthcareRemote, research institutions, analytics firms
CertificationsData analysis, Python programming certificationsData analysis, R programming certifications
Common UsageData cleaning, automation, machine learningStatistical modeling, data visualization, reporting

Both roles involve data analysis in remote settings, with Python-focused roles emphasizing automation and machine learning, while R roles focus more on statistical modeling and visualization. The choice depends on the specific tools and tasks preferred by the employer or industry.

Public Health Data Analyst

Public Health Data Analyst

CyberData Technologies

Herndon, VA โ€ข Remote

Other

Posted 14 hours ago


Job description

Public Health Data Analyst
DNPAO Data Analysis and Management Project

Location: Remote (Atlanta Metropolitan Area Preferred)

*** Must be able to Obtain and Maintain a CDC Public Trust Clearance ***


Job Description

CyberData Technologies is seeking an experienced Public Health Data Analyst to support the Centers for Disease Control and Prevention (CDC), Division of Nutrition, Physical Activity, and Obesity (DNPAO). The selected candidate will provide advanced data management, statistical analysis, and epidemiologic support for public health initiatives focused primarily on breastfeeding, child nutrition, obesity prevention, and related chronic disease prevention programs.ย  This position will support DNPAO's efforts to generate high-quality, reproducible analyses and reports using large national public health datasets. The successful candidate will create and manage complex data systems, develop statistical analysis plans, perform sophisticated epidemiologic analyses, and communicate findings that inform public health programs, policy decisions, and national surveillance activities.ย  The ideal candidate will possess extensive experience working with complex survey data, large public health datasets, advanced statistical methods, and data management practices within federal public health environments.


Job Responsibilities

Data Analysis Planning

  • Develop comprehensive statistical analysis plans that support epidemiologic research and surveillance activities.
  • Identify research questions and hypotheses aligned with programmatic and policy objectives.
  • Determine appropriate inclusion and exclusion criteria for analyses.
  • Evaluate datasets and identify variables necessary to address research objectives.
  • Select appropriate statistical methodologies and software tools to support analyses.
  • Develop table shells, data specifications, and documentation supporting analytical activities.
  • Document all data preparation, transformation, and analytical processes to ensure reproducibility and transparency.

Data Management

  • Collect, review, code, validate, manipulate, and maintain large public health datasets.
  • Create and maintain data dictionaries and metadata documentation.
  • Develop and manage working datasets and analysis files.
  • Perform data cleaning, quality assurance, validation, and integrity checks.
  • Manage data related to breastfeeding, child nutrition, obesity, and other DNPAO program areas.
  • Maintain and analyze data from national surveillance systems and public-use datasets.
  • Access and utilize data files, questionnaires, and documentation from CDC and National Center for Health Statistics (NCHS) data collection systems.

Statistical Analysis and Interpretation

  • Conduct univariable, bivariable, and multivariable statistical analyses using complex survey data methodologies.
  • Analyze large national datasets and interpret findings for technical and non-technical audiences.
  • Produce recurring surveillance reports, statistical summaries, dashboards, and data visualizations.
  • Support annual Healthy People 2030 reporting activities related to maternal and child health indicators.
  • Develop quarterly updates for DNPAO Data, Trends, and Maps reporting systems.
  • Respond to federal partner requests, state-level inquiries, and ad hoc data requests.
  • Conduct analyses using longitudinal and cross-sectional datasets to support public health decision-making.
  • Prepare technical reports, manuscripts, presentations, and summary documents communicating analytical findings.
  • Collaborate with CDC scientists, epidemiologists, program staff, and external stakeholders to support surveillance and evaluation activities.

Public Health Surveillance Support

  • Support analyses involving national public health surveillance systems and large-scale survey datasets.
  • Provide technical expertise related to breastfeeding surveillance, nutrition monitoring, obesity prevention, physical activity, and maternal and child health indicators.
  • Assist in developing evidence-based recommendations that support public health programs and policy initiatives.
  • Ensure analytical methods adhere to CDC standards and best practices for complex survey analysis.

Required Skills and Experience

  • Master's degree or higher in Epidemiology, Biostatistics, Public Health, Statistics, Data Science, Health Sciences, or a related quantitative field.
  • Minimum of three (3) years of professional experience supporting epidemiologic research, public health surveillance, statistical analysis, or related analytical activities.
  • Advanced expertise using statistical software including SAS, SPSS, R, SUDAAN, Epi Info, or similar analytical tools.
  • Extensive experience managing and analyzing large, complex survey datasets that utilize weighting, clustering, and stratification methodologies.
  • Strong knowledge of epidemiologic methods, surveillance systems, and quantitative public health research.
  • Demonstrated experience developing statistical analysis plans and managing large datasets from acquisition through reporting.
  • Experience conducting multivariable statistical analyses and interpreting findings for public health applications.
  • Ability to independently manage multiple analytical projects and respond to ad hoc data requests.
  • Strong written and verbal communication skills, including technical report development and presentation of findings.
  • Experience developing reproducible analytical workflows and maintaining detailed documentation.

Preferred Skills and Experience

  • Experience supporting the Centers for Disease Control and Prevention (CDC) or other federal public health agencies.
  • Experience analyzing National Health and Nutrition Examination Survey (NHANES) data.
  • Experience working with the National Immunization Survey (NIS), National Survey of Childrenโ€™s Health, National Vital Statistics System (NVSS), Youth Risk Behavior Surveillance System (YRBSS), or similar national surveillance systems.
  • Knowledge of breastfeeding surveillance, maternal and child health, nutrition, obesity prevention, and chronic disease epidemiology.
  • Experience supporting Healthy People objectives, public health surveillance reporting, and policy-related analyses.
  • Familiarity with CDC data management standards and public-use datasets.
  • Experience developing data visualizations, dashboards, and automated reporting processes.
  • Experience working with Azure products (i.e. Databricks), Python and GitHub.