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Data Science Jobs in Berlin, MD (NOW HIRING)

La Red Health Center Inc

Data Analyst

Georgetown, DE · On-site

Bachelor's degree in health informatics, Data Science, Statistics, Public Health or a related field. * Minimum of 2-3 of Data Analysis experience in a healthcare environment Language Skills:

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Data Science information

See Berlin, MD salary details

$36K

$117.9K

$188.7K

How much do data science jobs pay per year?

As of Aug 25, 2026, the average yearly pay for data science in Berlin, MD is $117,871.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $130,600.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
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Infographic showing various Data Science job openings in Berlin, MD as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $117,871 per year, or $56.7 per hour.

Data Analyst

La Red Health Center Inc

Georgetown, DE • On-site

Full-time

Posted 17 days ago

Job description

Description:

Job Summary:

This Data Analyst is responsible for collecting, cleaning, analyzing, and transforming complex clinical, financial, and operational datasets into actionable insights. The position supports reporting, analytics, evaluation and performance improvement efforts across the organization.

Essential Responsibilities:

The following duties are not intended to serve as a comprehensive list of all duties performed by all associates in this position. The duties listed are intended to provide a representative summary of the major duties and responsibilities. The incumbent may be required to perform additional, position-specific duties as assigned by their manager and/or LRHC Leadership.

Regulatory Reporting & Compliance

  • UDS Reporting: Manage the aggregation, validation, and submission of annual HRSA Uniform Data System (UDS) tables.
  • PCMH Maintenance: Track, analyze, and report on electronic clinical quality measures (eCQMs) required for Patient-Centered Medical Home (PCMH) recognition.
  • State & Federal Grants: Author data queries and generate structured reporting assets for federal, state, and private grant compliance (e.g., HRSA, Delaware DHSS).

Data Analysis & Business Intelligence

  • Dashboard Development: Design, deploy, and maintain interactive performance dashboards using Power BI or Tableau for clinical and administrative leadership.
  • EHR Optimization: Extract complex datasets from the Electronic Health Record (EHR) system (e.g., Epic/OCHIN, eClinicalWorks) utilizing SQL queries.
  • Ad-Hoc Analysis: Provide timely, data-driven answers to operational and clinical inquiries from executive leadership.

Quality Improvement (QI) Support

  • Clinical Metrics: Identify gaps in preventive care, chronic disease management, and social determinants of health (SDOH).
  • Population Health: Stratify high-risk patient panels to support care coordination and population health management.
  • Workflow Validation: Partner with clinical staff to evaluate data capture workflows and eliminate data entry errors at the point of care


Requirements:

Qualifications:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or competency required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

Education/Experience/Certification:

  • Required: Bachelor’s degree in health informatics, Data Science, Statistics, Public Health or a related field.
  • Minimum of 2–3 of Data Analysis experience in a healthcare environment

Language Skills:

Bilingual (English/Spanish) preferred


Skills and Competencies:

Technical Skills

  • Knowledge of HRSA Uniform Data System reporting
  • SQL: Advanced proficiency in writing SQL queries for relational databases.
  • BI Tools: Strong development experience using Power BI, Tableau, or equivalent visualization platforms.
  • EHR Systems: Experience extracting and interpreting data directly from health IT platforms (e.g., Epic/OCHIN, eClinicalWorks, NextGen).
  • Spreadsheets: Mastery of Microsoft Excel, including complex formulas, VLOOKUPs, and pivot tables.

Knowledge & Compliance

  • Regulations: Strong foundational understanding of HIPAA regulations and data security practices regarding Protected Health Information (PHI).
  • Healthcare Coding: Familiarity with standard clinical coding systems, including ICD-10, CPT, HCPCS, and LOINC.

Equipment Operated:

Wide range of office equipment.

Enterprise server infrastructure, firewalls, network switches, and access control hardware.

High proficiency and daily use of enterprise software suites (e.g., Microsoft 365, Active Directory, Epic EHR, and helpdesk ticketing workflows).


Mental/Physical Requirements:

Frequent sitting or standing for long periods while using a computer