Cyberhill Partners, LLC
Senior Data Scientist (PhD)
Cyberhill Partners, LLC, Snowflake, Arizona, United States, 85937
Cyberhill Partners, LLC Senior Data Scientist (PhD) Remote·Full time Company website Apply for Senior Data Scientist (PhD)
Senior Data Scientist with a PhD and deep expertise in machine learning. About Cyberhill Partners, LLC
Cyberhill Partners is a professional services firm specializing in engineering future-state software solutions for Fortune 500 companies. Focusing on cybersecurity, cloud computing, data analytics, and AI, Cyberhill provides comprehensive implementation services that drive success and security. With over 800 complex cybersecurity implementations completed, Cyberhill is an established and trusted services partner. Description
About Cyberhill Partners
Cyberhill Partners is a cutting-edge technology services firm specializing in
data, artificial intelligence, and cybersecurity . We work with Fortune 500 enterprises to solve high-impact business problems through advanced analytics and intelligent systems. Our team is composed of domain experts, engineers, and data scientists who are passionate about pushing the boundaries of what AI can do. We are expanding our AI & Data Science practice and are looking for a
Senior Data Scientist with a PhD
and deep expertise in machine learning to help shape and deliver next-generation solutions. Role Overview
As a
Senior Data Scientist , you will lead the development of advanced machine learning models and analytical solutions for Cyberhill’s enterprise clients. You’ll work on projects involving structured and unstructured data, predictive modeling, optimization, NLP, and generative AI—delivering real-world impact across industries like healthcare, energy, and manufacturing. This is a hands-on, client-facing role ideal for someone who combines academic rigor with strong business intuition and is comfortable owning end-to-end data science workflows. Key Responsibilities
Design, build, and validate advanced machine learning models (e.g., supervised, unsupervised, deep learning, reinforcement learning) for real-world problems. Apply techniques such as NLP, time series forecasting, anomaly detection, and recommendation systems. Client-Facing Delivery
Engage directly with clients to understand business challenges and translate them into analytical use cases. Communicate complex technical concepts to non-technical stakeholders in a clear, compelling way.
Work with engineers to acquire, process, and transform large datasets. Conduct feature engineering and exploratory data analysis (EDA) to uncover key insights. Stay at the forefront of AI/ML research and identify opportunities to apply novel methods. Contribute to internal R&D efforts and help shape Cyberhill’s data science roadmap. Provide technical mentorship to junior data scientists and collaborate across teams to elevate overall data maturity. Required Qualifications
PhD in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. 5+ years of experience building ML models in a production or applied research environment. Strong programming skills in
Python
(e.g., pandas, scikit-learn, TensorFlow, PyTorch, XGBoost, etc.). Proficient in SQL and working with cloud platforms (e.g., AWS, GCP, or Azure). Deep understanding of statistical modeling, machine learning algorithms, and MLOps best practices. Experience working with large, messy, real-world datasets and delivering business value from data. Excellent communication skills with the ability to interact with technical and executive stakeholders. Preferred Qualifications
Experience in one or more of the following areas: NLP, generative AI, computer vision, graph analytics, causal inference, or time series forecasting. Prior consulting experience or client-facing roles in a services environment. Familiarity with enterprise data platforms (e.g., Databricks, Snowflake) and data visualization tools. What We Offer
Competitive salary: $150,000 – $250,000/year (based on experience and performance) Opportunity to work on high-impact, cutting-edge AI initiatives with top-tier enterprises A collaborative, research-oriented environment with industry and academic leaders Flexible work arrangements (remote/hybrid) Equity potential and performance bonuses for top contributors
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Senior Data Scientist with a PhD and deep expertise in machine learning. About Cyberhill Partners, LLC
Cyberhill Partners is a professional services firm specializing in engineering future-state software solutions for Fortune 500 companies. Focusing on cybersecurity, cloud computing, data analytics, and AI, Cyberhill provides comprehensive implementation services that drive success and security. With over 800 complex cybersecurity implementations completed, Cyberhill is an established and trusted services partner. Description
About Cyberhill Partners
Cyberhill Partners is a cutting-edge technology services firm specializing in
data, artificial intelligence, and cybersecurity . We work with Fortune 500 enterprises to solve high-impact business problems through advanced analytics and intelligent systems. Our team is composed of domain experts, engineers, and data scientists who are passionate about pushing the boundaries of what AI can do. We are expanding our AI & Data Science practice and are looking for a
Senior Data Scientist with a PhD
and deep expertise in machine learning to help shape and deliver next-generation solutions. Role Overview
As a
Senior Data Scientist , you will lead the development of advanced machine learning models and analytical solutions for Cyberhill’s enterprise clients. You’ll work on projects involving structured and unstructured data, predictive modeling, optimization, NLP, and generative AI—delivering real-world impact across industries like healthcare, energy, and manufacturing. This is a hands-on, client-facing role ideal for someone who combines academic rigor with strong business intuition and is comfortable owning end-to-end data science workflows. Key Responsibilities
Design, build, and validate advanced machine learning models (e.g., supervised, unsupervised, deep learning, reinforcement learning) for real-world problems. Apply techniques such as NLP, time series forecasting, anomaly detection, and recommendation systems. Client-Facing Delivery
Engage directly with clients to understand business challenges and translate them into analytical use cases. Communicate complex technical concepts to non-technical stakeholders in a clear, compelling way.
Work with engineers to acquire, process, and transform large datasets. Conduct feature engineering and exploratory data analysis (EDA) to uncover key insights. Stay at the forefront of AI/ML research and identify opportunities to apply novel methods. Contribute to internal R&D efforts and help shape Cyberhill’s data science roadmap. Provide technical mentorship to junior data scientists and collaborate across teams to elevate overall data maturity. Required Qualifications
PhD in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. 5+ years of experience building ML models in a production or applied research environment. Strong programming skills in
Python
(e.g., pandas, scikit-learn, TensorFlow, PyTorch, XGBoost, etc.). Proficient in SQL and working with cloud platforms (e.g., AWS, GCP, or Azure). Deep understanding of statistical modeling, machine learning algorithms, and MLOps best practices. Experience working with large, messy, real-world datasets and delivering business value from data. Excellent communication skills with the ability to interact with technical and executive stakeholders. Preferred Qualifications
Experience in one or more of the following areas: NLP, generative AI, computer vision, graph analytics, causal inference, or time series forecasting. Prior consulting experience or client-facing roles in a services environment. Familiarity with enterprise data platforms (e.g., Databricks, Snowflake) and data visualization tools. What We Offer
Competitive salary: $150,000 – $250,000/year (based on experience and performance) Opportunity to work on high-impact, cutting-edge AI initiatives with top-tier enterprises A collaborative, research-oriented environment with industry and academic leaders Flexible work arrangements (remote/hybrid) Equity potential and performance bonuses for top contributors
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