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

AI Data Engineer - Senior Consultant

Rochester, NY · On-site

$104.60K - $142.10K/yr

Qualifications : Required : • Bachelor's degree in a STEM field (e.g., Computer Science ... PhD) and/or relevant certifications (cloud and AI/ML). • 4+ years of experience with Human ...

AI Data Engineer - Senior Consultant

Rochester, NY · Hybrid

$103.10K - $141.60K/yr

Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science ... Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML). * 4+ years of experience ...

Bachelor's degree in Life Sciences, Engineering, or a related technical discipline required. * 7+ ... Advanced degree (MS, PhD, MBA, or equivalent) in a relevant discipline. * Experience implementing ...

Quantum Postdoc Associate

Batavia, NY · On-site

$69.80K - $92.60K/yr

Participating in experimental measurements, data acquisition, data analysis, and interpretation of ... PhD in Physics, Engineering, Applied Physics, Electrical Engineering, or a related field.

... members to bring world-class scientific discoveries to real-world applications. With the ... Several technical levels require different qualifications from BS to PhD. The desired degrees are ...

... members to bring world-class scientific discoveries to real-world applications. With the ... Several technical levels require different qualifications from BS to PhD. The desired degrees are ...

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Data Science Phd information

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

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by Data Science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What is a Data Science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.
What are popular job titles related to Data Science Phd jobs in Rochester, NY? For Data Science Phd jobs in Rochester, NY, the most frequently searched job titles are:
What cities near Rochester, NY are hiring for Data Science Phd jobs? Cities near Rochester, NY with the most Data Science Phd job openings:
Infographic showing various Data Science Phd job openings in Rochester, NY as of May 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 95% Physical, 3% Hybrid, and 2% Remote job distribution.
AI Data Engineer - Senior Consultant

AI Data Engineer - Senior Consultant

Deloitte

Rochester, NY • On-site

$104.60K - $142.10K/yr

Full-time

Posted 12 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

Job Summary:
Deloitte's Human Capital team is seeking an AI Engineer Senior Consultant to build and operate the data and AI foundations that enhance Human Capital AI products and analytics. This hands-on role involves designing and delivering secure, scalable AI solutions in collaboration with various teams to support model training and real-time inference.
Responsibilities:
• Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
• Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
• Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
• Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).
• Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk stakeholders.
• Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring; right-sizing, query tuning, LLM token/cost telemetry).
• Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and runbooks.
Qualifications:
Required:
• Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
• 4+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
• 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
• 4+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
• 4+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
• 4+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
• 4+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
• 4+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
• Ability to travel 0-25%, on average, based on client and project needs.
• Limited immigration sponsorship may be available
Preferred:
• Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
• 4+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
• 4+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
• 4+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
• 4+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
• 4+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
• 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
• 4+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
• 4+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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