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Data Visualisation Analyst Jobs (NOW HIRING)

Lynx Analytics

Senior Data Scientist (US)

New York, NY · On-site

Strong hands-on proficiency in Python for data analysis, modelling (PyTorch, TensorFlow, or JAX ... Excellent verbal and written communication skills, with strong data visualisation ability and ...

The Sustainability Grid

$60 - $80/hr

Business Analyst, Worldwide Grocery Sustainability at Amazon Amazon is a global technology and ... Data visualisation and business intelligence tools. Preferred Qualifications Amazon lists the ...

24-Mag Llc

$100 - $125/hr

... data visualisation, KPI analysis, and quantitative business insights. This role focuses on reviewing professional documents, spreadsheets, dashboards, and presentation materials related to business ...

Daniels Health

HRIS Workday Analyst - Reporting

Chicago, IL · On-site +1

$79K - $101K/yr

Excel, Power BI, Tableau) for supplementary analysis and data visualisation. * HR, data or systemsrelated qualification (e.g. CIPD, HR analytics certification, or equivalent) is beneficial but not ...

Daniels Health

HRIS Workday Analyst - Reporting

Chicago, IL · On-site +1

$79K - $101K/yr

Excel, Power BI, Tableau) for supplementary analysis and data visualisation. * HR, data or systems‑related qualification (e.g. CIPD, HR analytics certification, or equivalent) is beneficial but not ...

ZURU

Business Analyst

Minneapolis, MN · On-site

Apply now to join ZURU as a Business Analyst! ZURU is in a phase of explosive growth, driven by ... data visualisation tools like Power BI or Tableau. The Person We Are Looking For Beyond the ...

Syngenta Group

Data Partnerships Lead

Durham, NC · On-site

You will connect business needs with data, digital and analytics solutions-helping teams improve ... visualisation or AI is an advantage. Qualifications Additional Information This is a global role ...

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Data Visualisation Analyst information

See salary details

$34K

$82.6K

$136K

How much do data visualisation analyst jobs pay per year?

As of Sep 8, 2026, the average yearly pay for data visualisation analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What does a data visualisation analyst do?

A Data Visualisation Analyst is responsible for transforming complex data sets into clear and visually engaging charts, graphs, and dashboards. They use specialized tools and software to help organizations understand trends, patterns, and insights from their data. By communicating findings visually, they enable stakeholders to make informed decisions quickly and effectively. Their role often involves collaborating with data scientists, business analysts, and decision-makers to ensure that visualizations meet business needs.

What are some common challenges data visualisation analysts face when presenting insights to non-technical stakeholders?

Data Visualisation Analysts often encounter the challenge of translating complex data findings into clear, actionable visuals that resonate with non-technical audiences. It can be difficult to strike the right balance between detail and simplicity, ensuring that key insights are not lost while avoiding overwhelming the audience. Effective communication and tailoring presentations to the audience's level of data familiarity are critical for success. Additionally, Analysts may need to address stakeholder questions on data sources or methodologies, so being prepared with accessible explanations is essential.

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

To thrive as a Data Visualisation Analyst, you need strong analytical skills, proficiency in statistics, and a solid grasp of data interpretation, often supported by a degree in mathematics, computer science, or a related field. Expertise in visualization tools like Tableau, Power BI, and proficiency in SQL or Python are typically required. Attention to detail, creativity, and the ability to communicate complex information simply are standout soft skills in this role. These skills are crucial for transforming raw data into actionable insights and ensuring stakeholders can make informed, data-driven decisions.

What is the difference between Data Visualisation Analyst vs Data Analyst?

AspectData Visualisation AnalystData Analyst
Primary FocusCreating visual representations of data to communicate insightsAnalyzing data sets to identify trends and patterns
Skills & ToolsData visualization tools (Tableau, Power BI), graphic designStatistical analysis, SQL, Excel
Work EnvironmentBusiness intelligence teams, data departmentsData analysis teams, research departments
CertificationsTableau Desktop Specialist, Power BI certificationsGoogle Data Analytics, Microsoft Certified Data Analyst

While both roles involve working with data, a Data Visualisation Analyst primarily focuses on creating visual tools to communicate data insights effectively, whereas a Data Analyst concentrates on analyzing data to uncover trends and inform decision-making. The roles often overlap, but their core responsibilities differ in emphasis on visualization versus analysis.

What cities are hiring for Data Visualisation Analyst jobs?

Cities with the most Data Visualisation Analyst job openings:

What states have the most Data Visualisation Analyst jobs?

States with the most job openings for Data Visualisation Analyst jobs include:

What are popular job titles related to Data Visualisation Analyst jobs?

For Data Visualisation Analyst jobs, the most frequently searched job titles are:

Data Visualisation Analyst jobs near you
Infographic showing various Data Visualisation Analyst job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Senior Data Scientist (US)

New York, NY • On-site

Lynx Analytics
See more jobs at Lynx Analyticsexternal

Full-time

Posted 20 days ago

Key responsibilities

  • Design and deliver end-to-end data science solutions combining classical modelling, data transformation, and Generative AI / LLM techniques.

  • Work with large datasets across different systems to perform data ingestion, transformation, modelling, and validation.

  • Present results to stakeholders, including C-level audiences, and guide junior team members in data science workstreams.

Job description

ROLE SUMMARY
We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions.
KEY RESPONSIBILITIES
Solution Design & Delivery
  • Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques.
  • Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation.
  • Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation.

Client Communication & Leadership
  • Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives.
  • Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members.
  • Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations.

Knowledge Building
  • Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work.
  • Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice.

SKILLS, QUALIFICATIONS AND EXPERIENCE
  • 8+ years of overall experience in data science, with a track record of leading analytical workstreams independently.
  • Degree in Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field; MSc or PhD preferred.
  • Solid grounding in probability theory, statistics, and core data science algorithms, with applied experience in areas such as customer retention and campaign management.
  • Strong hands-on proficiency in Python for data analysis, modelling (PyTorch, TensorFlow, or JAX), and productionising code.
  • Strong SQL, and comfort working across common data stores (relational, columnar/warehouse, and vector databases).
  • Git and GitHub proficiency, including branching workflows and code review; experience with GitHub Actions (or equivalent CI/CD) preferred.
  • Hands-on experience designing and building agentic LLM applications - tool calling, multi-step orchestration, and state management - using at least one modern framework (e.g., LangGraph, Pydantic AI, AWS Bedrock AgentCore, Google ADK, or the OpenAI Agents SDK), beyond simple prompt-and-response use of LLM APIs.
  • Preferred: practical depth in one or more of MCP-based tool integration, RAG and embedding pipelines (including vector stores), model fine-tuning and RL-based post-training, and LLM guardrails and evaluation (e.g., Ragas, DeepEval, Langfuse, or similar).
  • Experience with at least one major cloud platform (AWS, GCP, or Azure); Docker and basic containerised deployment preferred.
  • Comfortable working with very large, complex datasets residing in different data stores and formats.
  • Excellent verbal and written communication skills, with strong data visualisation ability and experience presenting to senior, non-technical stakeholders.
  • Demonstrated leadership potential and the presence to guide junior team members and represent the company with clients.
  • Nice to have:
    • Software engineering hygiene (preferred): typed Python (Pydantic), testing with pytest, packaging, and dependency management (uv).
    • Experience shipping LLM applications to production, including observability and cost/latency management (e.g., Langfuse, Phoenix, or similar LLMOps tooling).
    • Experience in the life sciences industry is preferred.

KEY COMPETENCIES
  • Executive Communication: Translates complex Data Science solutions into plain language for C-level and non-technical stakeholders.
  • Technical Depth: Brings rigorous statistical and modelling judgement, paired with fluency in modern GenAI/LLM approaches.
  • Discretion & Integrity: Handles sensitive client and internal information with professionalism and sound judgement.
  • Leadership & Charisma: Guides junior colleagues day to day, even without a formal management title, and takes pride in their growth.
  • Collaboration: A team player who builds strong working relationships across delivery teams, PMO, and clients.

WHY YOU WILL LOVE IT HERE
  • Work on real-world AI and advanced analytics solutions with measurable business impact.
  • Collaborate with a global team of engineers and data scientists.
  • Exposure to diverse industries, modern cloud platforms, and cutting-edge AI technologies.
  • A collaborative culture that values real outcomes.
  • High ownership, zero micromanagement.
  • Rapid learning opportunities and diverse challenges.
  • Flat organisational hierarchy with high visibility and accessibility to our leaders.

Apply