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Phd Data Scientist Jobs in Rochester, NY (NOW HIRING)

Sr. Solutions Architect AI

Rochester, NY · On-site

$170K - $195K/yr

Bachelor's degree in Computer Science, Data Science, or a related field (Master's or PhD preferred). * A "Builder" Mindset: A startup mentality, a strategic approach to problem-solving, and a genuine ...

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Phd Data Scientist information

See Rochester, NY salary details

$45.4K

$162.8K

$240.3K

How much do phd data scientist jobs pay per year?

As of Aug 2, 2026, the average yearly pay for phd data scientist in Rochester, NY is $162,818.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,700.00 and $167,700.00 per year, depending on experience, location, and employer.

What are PhD Data Scientists?

PhD Data Scientists are professionals who have earned a doctoral degree (PhD) in a relevant field, such as computer science, statistics, mathematics, or engineering, and work in roles focused on analyzing and interpreting complex data. They leverage advanced research skills, deep theoretical knowledge, and expertise in data modeling to solve challenging problems, build predictive models, and derive actionable insights for organizations. PhD Data Scientists often contribute to cutting-edge projects, publish research, and help bridge the gap between academic research and practical, real-world applications.

What is the difference between Phd Data Scientist vs Data Analyst?

AspectPhd Data ScientistData Analyst
Required CredentialsPhD or Master's in Data Science, Statistics, or related fieldBachelor's or Master's in related field, often with certifications
Work EnvironmentResearch-focused, complex modeling, advanced analyticsBusiness reporting, data visualization, basic analysis
Employer & Industry UsageTech, academia, research institutions, large corporationsBusiness, marketing, finance, healthcare

Phd Data Scientists typically have advanced degrees and focus on complex modeling and research, while Data Analysts handle more straightforward data reporting and visualization tasks. Both roles are essential in data-driven organizations but differ in scope and expertise.

What are the key skills and qualifications needed to thrive as a PhD Data Scientist, and why are they important?

To thrive as a PhD Data Scientist, you need advanced expertise in statistics, machine learning, and data analysis, typically backed by a PhD in a quantitative field. Proficiency with programming languages like Python or R, experience with big data tools (e.g., Hadoop, Spark), and familiarity with cloud platforms and version control systems are commonly required. Strong problem-solving skills, communication abilities, and the capacity to explain complex concepts to non-technical stakeholders are crucial soft skills. These skills and qualities are essential for extracting actionable insights from complex datasets and driving data-informed decision-making in organizations.

What are some common challenges PhD Data Scientists face when transitioning from academia to industry roles?

PhD Data Scientists often encounter challenges when moving from academia to industry, such as adapting to faster project timelines, prioritizing business impact over exploratory research, and communicating complex findings to non-technical stakeholders. In industry, there is a greater emphasis on collaborative teamwork and delivering actionable insights that align with organizational goals. Building skills in agile development, stakeholder engagement, and product-focused thinking can help smooth the transition and ensure success in a corporate environment.
What job categories do people searching Phd Data Scientist jobs in Rochester, NY look for? The top searched job categories for Phd Data Scientist jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Phd Data Scientist jobs? Cities near Rochester, NY with the most Phd Data Scientist job openings:
Infographic showing various Phd Data Scientist job openings in Rochester, NY as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $162,818 per year, or $78.3 per hour.

AI Training Specialist - Life Sciences

micro1 AI

Rochester, NY • Remote

$90 - $120/hr

Part-time

Posted 5 days ago


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.