Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Director, Data Science

Senior Proactive Engineer

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist

Consulting Principal AWS Cloud Engineer

Responsibilities: <ul><li>Lead experimentation and model development for AI/ML solutions in legal products.</li><li>Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics, Mathematics).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Proven experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Ability to define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Able to analyze large-scale legal datasets to extract insights and improve model performance.</li></ul>

Responsibilities: <ul><li>Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Education: Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Strong experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Strong foundation in statistics, modeling, and large-scale text processing.</li></ul>

Responsibilities: Strategic Leadership:&nbsp; <ul><li>Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.</li></ul> Team Management:&nbsp; <ul><li>Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.</li></ul> Advanced Research Direction:&nbsp; <ul><li>Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage.</li></ul> Machine Learning and AI Solutions:&nbsp; <ul><li>Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.</li></ul> Data Collection and Preparation:&nbsp; <ul><li>Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.</li></ul> Data Visualization Strategy:&nbsp; <ul><li>Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.</li></ul> Cross-functional Collaboration:&nbsp; <ul><li>Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.</li></ul> Model Deployment and MLOps:&nbsp; <ul><li>Oversee the deployment of machine learning models into pro duction environments, ensuring scalability and reliability.</li></ul> Documentation Standards:&nbsp; <ul><li>Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.</li></ul> Budget and Resource Management:&nbsp; <ul><li>Manage departmental budget, resource allocation, and infrastructure needs for data science operations.</li></ul> Ethical AI Governance:&nbsp; <ul><li>Develop and enforce ethical guidelines and best practices for AI development and deployment.</li></ul> Requirements: <ul><li>Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.</li><li>10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.</li><li>Demonstrated experience in managing and scaling data science teams of 15+ professionals.</li><li>Proven record of delivering high-impact AI and ML solutions that have driven significant business value.</li><li>Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.</li><li>Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.</li><li>Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.</li><li>Strong business acumen with the ability to translate complex technical concepts into business value.</li><li>Excellent communication and leadership skills, with experience presenting to executive leadership.</li><li>Experience working in a global or multicultural environment.</li><li>Record of successful collaboration with product, engineering, and business teams.</li><li>Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.</li></ul>

Responsibilities: <ul><li>Strategic Leadership: Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.</li><li>Team Management: Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.</li><li>Advanced Research Direction: Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage.</li><li>Machine Learning and AI Solutions: Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.</li><li>Data Collection and Preparation: Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.</li><li>Data Visualization Strategy: Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.</li><li>Cross-functional Collaboration: Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.</li><li>Model Deployment and MLOps: Oversee the deployment of machine learning models into pro duction environments, ensuring scalability and reliability.</li><li>Documentation Standards: Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.</li><li>Budget and Resource Management: Manage departmental budget, resource allocation, and infrastructure needs for data science operations.</li><li>Ethical AI Governance: Develop and enforce ethical guidelines and best practices for AI development and deployment.</li></ul> Requirements: <ul><li>Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.</li><li>10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.</li><li>Demonstrated experience in managing and scaling data science teams of 15+ professionals.</li><li>Proven record of delivering high-impact AI and ML solutions that have driven significant business value.</li><li>Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.</li><li>Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.</li><li>Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.</li><li>Strong business acumen with the ability to translate complex technical concepts into business value.</li><li>Excellent communication and leadership skills, with experience presenting to executive leadership.</li><li>Experience working in a global or multicultural environment.</li><li>Record of successful collaboration with product, engineering, and business teams.</li><li>Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.</li></ul>

Responsibilities: <ul><li>Analyze DEX tool data to identify trends, predict issues, and propose proactive interventions to enhance employee digital experience.</li><li>Develop, test, and maintain scripts and tools using PowerShell and Python to automate repetitive tasks and improve system performance.</li><li>Work with data warehouses like Redshift and analytics platforms such as Databricks. Use SQL or another programming language to work with databases and create dashboards to extract insights and develop actionable recommendations.</li><li>Develop dashboards and reporting tools using SysTrack and Microsoft Power BI to provide visibility into key performance metrics.</li><li>Collaborate with IT Service Desk and Desktop Support Teams to identify opportunities for automation and efficiency improvements.</li><li>Proactively engage with stakeholders to understand business requirements and translate them into technical solutions.</li><li>Design and implement innovative ideas to enhance customer service and reduce the mean time to resolution (MTTR).</li><li>Act as a consultant to various teams, providing technical expertise in the use of DEX tools and scripting languages.</li><li>Lead initiatives to integrate new technologies or methodologies that improve the IT environment and employee satisfaction.</li><li>Conduct Root Cause Analysis (RCA) on recurring issues and propose permanent solutions.</li><li>Engage with vendor support resources to resolve complex technical challenges and evaluate new technologies.</li><li>Work with APIs to integrate and enhance system capabilities, ensuring seamless interaction between tools and platforms.</li></ul> Requirements: <ul><li>Proficiency in DEX tools like SysTrack, Nexthink, or similar platforms.</li><li>Strong coding skills in PowerShell and Python.</li><li>Hands-on experience with data analytics platforms, such as Databricks, and data warehouses like Redshift. Proficiency in SQL as a programming language for working with databases and creating dashboards.</li><li>Expertise in Microsoft Power Apps and Power BI for data visualization and automation.</li><li>Experience in working with APIs for system integration and enhancements.</li><li>Deep understanding of IT environments, including endpoint devices, software, and cloud-based tools.</li><li>Ability to interpret data and provide actionable insights to improve digital employee experience.</li><li>Strong problem-solving skills, with experience conducting RCA and developing innovative solutions.</li><li>Demonstrated ability to identify and act on trends and opportunities in emerging technologies.</li><li>Knowledge of IT Service Management frameworks (e.g., ITIL) and their practical application.</li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions</li><li>Lead the development of AI and machine learning models to solve business problems</li><li>Research, build, and deploy models based on shallow and deep machine learning</li><li>Train robust NLP-based models on large datasets</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs</li><li>Design APIs for disseminating data science outputs</li><li>Oversee the scaling of production systems to meet growing demands</li></ul> Requirements: <ul><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions.</li><li>Lead the development of AI and machine learning models to solve business problems.</li><li>Research, build, and deploy models based on shallow and deep machine learning.</li><li>Train robust NLP-based models on large datasets.</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs.</li><li>Design APIs for disseminating data science outputs.</li><li>Oversee the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Communicating findings and insights to stakeholders in a clear and concise manner.</li><li>Staying current with the latest AI and machine learning trends and technologies.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Driving best practices across our data science functions.</li><li>Setting strategy and team direction, with a clear vision for Data Science.</li><li>Working with product leaders to apply data science solutions.</li><li>Evaluating and creating new frameworks and defining methodologies and governance.</li><li>Leading small- to medium-sized teams (direct or indirect).</li><li>Setting a high-bar for model development.</li></ul> Requirements: <ul><li>Have substantial experience in a senior data scientist role.</li><li>Have experience in leading complex projects and customer relationships.</li><li>Have significant experience in managing larger Technical teams (direct or indirect).</li><li>Have experience in mentoring or training others, acting as a subject matter expert to guide colleagues.</li><li>Be a natural problem solver, able to take a lead in collaborating to resolve issues.</li><li>Have excellent communication skills and the ability to convey information clearly to senior stakeholders.</li></ul> Highly Desired Skills and Experience: <ul><li>PhD or Masters degree in Computer Science, Mathematics, Statistics, or a related field.</li><li>7-10+ years of experience in AI and machine learning.</li><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

Responsibilities: <ul><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems. Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units. Overseeing the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units.</li><li>Overseeing the scaling of production systems to meet growing demands.</li></ul> Requirements: <ul><li>Possess an advanced or Masters education in Computer Science, Mathematics, Statistics, or a related field. Have experience working directly with large language models and transformer-based architectures including BERT, RoBERTa, T5 etc.</li><li>Be proficient in working with big data technologies and tools like Hadoop, Spark, or AWS.</li><li>Have experience and knowledge of applying LLMs including ChatGPT, GPT 3.5, Claude, Mistral, etc.</li><li>Be a natural problem solver, able to lead and mentor junior data scientists, and collaborate with cross-functional teams.</li><li>Demonstrate proficient experience with machine learning algorithms, including deep learning, gradient boosting, and random forests Possess advanced programming skills in Python, R, or other relevant languages for data analysis.</li></ul>

Responsibilities: <ul><li>Demonstrated ability to drive cultural change and advocate for cloud transformation Key Responsibilities Cloud Strategy &amp; Leadership&nbsp;</li><li>Develop and implement a comprehensive AWS cloud strategy, ensuring alignment with business and technology goals.&nbsp;</li><li>Provide technical leadership and advocacy, championing cloud-native best practices and innovation.&nbsp;</li><li>Lead and drive architectural decisions, ensuring scalability, security, and operational efficiency.</li><li>Cloud Architecture &amp; Design&nbsp;</li><li>Architect secure, scalable, and highly available AWS cloud environments.&nbsp;</li><li>Develop and maintain enterprise-wide cloud blueprints, patterns, and frameworks to drive consistency.&nbsp;</li><li>Research and integrate emerging cloud technologies to foster continuous innovation. Infrastructure as Code &amp; Automation&nbsp;</li><li>Lead adoption and implementation of Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, and Helm.&nbsp;</li><li>Design and optimize CI/CD pipelines to streamline cloud deployments and operations.&nbsp;</li><li>Implement self-healing and automated failover mechanisms to enhance resilience and reliability.</li><li>Kubernetes &amp; Cloud-Native Technologies&nbsp;</li><li>Manage and optimize Kubernetes clusters (EKS, Helm, IAM) for scalability and security.&nbsp;</li><li>Define and enforce best practices for containerized applications and orchestration.&nbsp;</li><li>Improve Kubernetes networking, ingress, and observability solutions to enhance performance. Security &amp; Compliance&nbsp;</li><li>Establish and enforce security best practices for AWS environments, including IAM, WAF, Secret Manager, and encryption.&nbsp;</li><li>Implement zero-trust security models and secure multi-account AWS environments.&nbsp;</li><li>Conduct security audits, incident response, and ensure compliance with industry standards. Monitoring, Logging &amp; Reliability Engineering.</li><li>Deploy and manage monitoring tools (DataDog, Splunk, CloudWatch, Coralogix) to ensure visibility and observability.&nbsp;</li><li>Implement SRE principles to enhance system uptime, reliability, and efficiency.&nbsp;</li><li>Conduct post-mortem analysis and drive continuous improvements in cloud performance. Collaboration &amp; Thought Leadership&nbsp;</li><li>Work closely with software developers, system engineers, and security teams to design and implement cloud solutions.&nbsp;</li><li>Provide mentorship, training, and technical leadership to engineering teams.&nbsp;</li></ul> Requirements: <ul><li>10+ years of experience in IT, with at least 5+ years in AWS cloud engineering and architecture.</li><li>Deep understanding of AWS services, including EC2, EKS, RDS, S3, Lambda, VPC, IAM, Transit Gateway, and CloudFormation.&nbsp;</li><li>Expertise in Kubernetes (EKS, Helm, Daemon Sets, StatefulSets, Karpenter, external-dns, aws-cni).&nbsp;</li><li>Strong experience with Terraform, CloudFormation, and automation scripting (Bash, Python, PowerShell).&nbsp;</li><li>Hands-on experience managing CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps).&nbsp;</li><li>Proficiency in monitoring and logging tools (DataDog, Splunk, Coralogix, CloudWatch).&nbsp;</li><li>Strong networking and security knowledge (DNS, VPC, NAT, Security Groups, IAM).&nbsp;</li><li>Experience designing and developing scalable, production-grade software tools and automation scripts using Python. Preferred Certifications&nbsp;</li><li>AWS Certified Solutions Architect – Professional (or equivalent).&nbsp;</li><li>Additional certifications in Kubernetes (CKA), AWS Security, or DevOps are a plus. Leadership &amp; Soft Skills&nbsp;</li><li>Proven experience leading cloud architecture and strategy initiatives.&nbsp;</li><li>Ability to mentor and guide technical teams in a fast-paced, agile environment.&nbsp;</li><li>Strong problem-solving and troubleshooting skills in complex cloud environments.</li><li>Excellent communication skills with the ability to translate technical concepts for engineering, business, and executive stakeholders.&nbsp;</li></ul>

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9 raleigh Jobs found

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Director, Data Science

Director, Data Science

Senior Proactive Engineer

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist

Consulting Principal AWS Cloud Engineer

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9 raleigh Jobs found

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Director, Data Science

Director, Data Science

Senior Proactive Engineer

Senior Manager Data Science

Manager, Data Science (GNS)

Senior Data Scientist

Consulting Principal AWS Cloud Engineer

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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WhiteCrow is on a mission to connect companies with the best talent across the globe.