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Data Jobs in Olean, NY (NOW HIRING)

Dresser Utility Solutions

Sales Analyst

Bradford, PA · On-site

This role will be integral to sales operations across all markets, serving as an analytical partner by developing customer-facing tools, improving data quality, supporting sales enablement projects ...

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All JobsData JobsData Jobs in Olean, NY

Data information

See Olean, NY salary details

$40.7K

$145.9K

$215.2K

How much do data jobs pay per year?

As of Aug 4, 2026, the average yearly pay for data in Olean, NY is $145,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $150,300.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with data analysis tools like Excel, SQL, Python, and visualization platforms such as Tableau or Power BI is often required, and certifications in these tools can be advantageous. Attention to detail, critical thinking, and effective communication skills help analysts interpret data accurately and present actionable insights to stakeholders. These skills are crucial for transforming raw data into meaningful information that drives informed business decisions.

How does a data analyst typically collaborate with other departments within an organization?

Data Analysts frequently work cross-functionally, partnering with teams such as marketing, finance, operations, and product development. They gather requirements from stakeholders, interpret data to provide actionable insights, and often present findings in meetings or reports tailored to the audience's needs. Effective communication is key, as analysts must translate complex data into clear, impactful recommendations that guide business decisions. This collaborative environment fosters both learning and professional growth, as Data Analysts gain exposure to various business functions.

Is it hard to get a data job?

Getting a data job can be competitive, as it often requires strong skills in data analysis, programming, and tools like SQL or Python. Relevant experience, certifications, and a solid portfolio can improve chances of securing a position in this field.

What are different jobs that work with data?

Many different jobs require you to work with data. Occupational health and safety engineers, for instance, assess safety data collected by technicians and specialists and then design new processes to mitigate observed risks. Many careers in medical research, such as running clinical trials or developing new pharmaceuticals, require data collection and analysis. A large number of government labor and economic forecasting positions employ statisticians who analyze and model data based on surveys or raw information, such as the census or employment records.

What are careers in data?

Careers in data include roles such as data analyst, data scientist, data engineer, and database administrator. These jobs involve collecting, analyzing, and interpreting data to support decision-making, often requiring skills in programming, statistics, and data visualization tools like SQL, Python, or R.

What is the difference between Data vs Data Analyst?

AspectDataData Analyst
Required CredentialsTypically a degree in computer science, information technology, or related fieldsSame as Data, often requiring a degree in statistics, data science, or related areas
Work EnvironmentData professionals work in IT, data engineering, or database management settingsData analysts work in business, finance, marketing, and similar industries analyzing data for insights
Employer & Industry UsageUsed across tech, finance, healthcare, and more for data management and infrastructureCommonly employed in business sectors to interpret data and support decision-making

Data professionals focus on managing, storing, and processing data, while Data Analysts interpret and analyze data to generate insights. Both roles require similar educational backgrounds but differ in their primary functions within organizations.

More about Data jobs
What are the most commonly searched types of Data jobs in Olean, NY? The most popular types of Data jobs in Olean, NY are:
What cities near Olean, NY are hiring for Data jobs? Cities near Olean, NY with the most Data job openings:
Data jobs near you
Infographic showing various Data job openings in Olean, NY as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $145,855 per year, or $70.1 per hour.

Principal AI Platform / Agentic AI Architect (Town of Poland)

Intellias

Kennedy, NY • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Over 20 years of market experience, Intellias brings together technologists, creators and innovators in Europe, North and Latin America, and the Middle East. Join our international team and take the mission to solve the advanced tech challenges of tomorrow!

What project we have for you

We are seeking a highly experienced and hands-on Principal AI/ML Architect & Applied AI Lead to drive the design, development, and operationalization of enterprise-scale AI systems across research and production environments.

This role combines deep technical expertise in Machine Learning, Generative AI, distributed data systems, and cloud-native architectures with strategic leadership capabilities. The ideal candidate will lead complex AI initiatives end-to-end — from experimentation and research to scalable deployment in global enterprise environments.

The position requires a strong balance between:

  • technical leadership,
  • hands‑on implementation,
  • cross‑functional collaboration,
  • and mentoring of engineering and data science teams.
What you will do
  • Lead the design and implementation of AI/ML solutions across multiple business domains.
  • Drive enterprise adoption of Large Language Models (LLMs), Generative AI, NLP/NLU, and advanced analytics solutions.
  • Define AI architecture standards, MLOps best practices, and scalable deployment strategies.
  • Evaluate emerging AI technologies and identify opportunities for innovation and operational impact.
  • Translate research initiatives into production‑ready AI solutions.
  • Architect scalable distributed data‑processing systems capable of handling large‑scale datasets and real‑time pipelines.
  • Design and optimize cloud-native AI platforms using modern data engineering frameworks.
  • Lead cloud migration and modernization initiatives from on‑premises environments to Azure and/or AWS.
  • Implement efficient data pipelines leveraging Spark, Delta Lake, Databricks, Kubernetes, and containerized environments.
  • Ensure reliability, scalability, observability, and cost‑efficiency of AI infrastructure.
  • Design and implement enterprise‑grade chatbot and conversational AI platforms.
  • Lead development of Retrieval-Augmented Generation (RAG), agentic workflows, and LLM orchestration systems.
  • Define governance, evaluation, and monitoring strategies for GenAI systems.
  • Collaborate with research teams to operationalize LLM-based applications securely and responsibly.
  • Lead cross‑functional teams composed of data scientists, ML engineers, software engineers, and business stakeholders.
  • Mentor engineers and researchers in AI/ML best practices, architecture, and software engineering standards.
  • Coordinate global AI initiatives across distributed teams and multiple geographies.
  • Communicate technical concepts effectively to executive and non‑technical audiences.
  • Support innovation programs and AI adoption strategies across the organization.
What you need for this Requirements
  • Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
  • 10+ years of experience in AI/ML, data science, or distributed systems engineering.
  • Proven experience designing and deploying production‑grade AI solutions at enterprise scale.
  • Strong background in both research and industrial AI environments.
  • Experience leading global or distributed technical teams.
  • Generative AI systems
  • NLP / NLU
  • Databricks
  • SQL / NoSQL databases
  • Distributed computing architectures
  • Streaming and batch processing pipelines
  • Docker
  • Infrastructure-as-Code
  • MLOps frameworks
  • Python
  • Scala
  • Experience with AI governance and responsible AI practices.
  • Experience building AI platforms serving multiple teams or business units.
  • Experience optimizing cloud infrastructure and reducing operational costs.
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