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

AI Data Engineer - Senior Consultant

Rochester, NY · Hybrid

$103K - $141K/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 ...

Staff Scientist

Rochester, NY · On-site

$60K - $84K/yr

... data, education, experience, qualifications, expertise of the individual, and internal equity ... PhD in Biological sciences, molecular biology, cancer biology, biochemistry, or immunology ...

Staff Scientist

Rochester, NY · On-site

$60K - $84K/yr

... data, education, experience, qualifications, expertise of the individual, and internal equity ... PhD in Biological sciences, molecular biology, cancer biology, biochemistry, or immunology ...

... 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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Showing results 1-20

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 jobs can you get with a PhD in data science?

A PhD in data science qualifies individuals for advanced roles such as data scientist, machine learning engineer, research scientist, and data science consultant. These positions often require strong programming skills in Python or R, experience with big data tools, and the ability to develop complex models and algorithms. Graduates may work in industries like technology, finance, healthcare, or academia, often in research or leadership capacities.

What is the salary of a PhD in data science?

A PhD in data science typically earns between $100,000 and $150,000 annually in the United States, depending on experience, industry, and location. Senior roles or positions in high-demand sectors can offer higher compensation, often exceeding $160,000. Advanced skills in machine learning, statistical analysis, and programming are highly valued in this field.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

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.

Is doing a PhD in data science worth it?

A PhD in data science can lead to advanced roles in research, academia, or specialized industry positions requiring deep expertise in machine learning, statistical analysis, and programming. It typically involves several years of study and research, which can increase earning potential and job opportunities but also requires significant time and effort investment. The decision depends on career goals and whether advanced research or teaching roles align with your interests.
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 June 2026, with employment types broken down into 92% Full Time, 7% Part Time, and 1% Contract. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution.
AI Data Engineer - Senior Consultant

AI Data Engineer - Senior Consultant

Deloitte

Rochester, NY • Hybrid

$103K - $141K/yr

Other

Posted 5 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

AI Engineer Senior Consultant

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on August 30, 2026

Work You'll Do:

As an AI Engineer Senior Consultant, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

Key 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.

The Team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Required Qualifications:

  • 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 Qualifications:

  • 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.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 to $208,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Milwaukee, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY26 #IIOFY26

Qualifications:

AI Engineer Senior Consultant

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on August 30, 2026

Work You'll Do:

As an AI Engineer Senior Consultant, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

Key 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.

The Team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Required Qualifications:

  • 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 Qualifications:

  • 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.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 to $208,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dall...


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