Data Analytics Manager- Data Lake

Manager role focused on leading teams in delivering cyber analytics, AI, and security operations solutions. This involves architecting and deploying AI/ML technologies for cyber defense, managing data platforms, and guiding clients on their AI/Analytics journey, with a strong emphasis on using AI development tools and techniques for cybersecurity use cases.

What you'd actually do

  1. Lead the design and modernization of large-scale cyber data and analytics programs that promote organizational intelligence, provide embedded capacity, and implement scalable as-a-service operating models
  2. Architect and deploy advanced cyber big data and AI technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, and platforms such as Splunk, CrowdStrike, and Palo Alto
  3. Oversee day-to-day operations, maintenance, and ongoing enhancement of data platforms and applications, including governance and AI-enabled Data Ops capabilities
  4. Help clients mature their AI and Analytics journey by shaping roadmaps, scaling use cases, and aligning cyber analytics investments to business and operational outcomes

Skills

Required

  • 6+ years of relevant analytics consulting or industry experience
  • 4+ years of experience with AI development tools such as vector databases (Pinecone, Elastic, etc.) and AI development frameworks (LangChain, CrewAI, etc.)
  • 4+ years of experience in statistical analysis, machine learning, and data mining techniques
  • 4+ years of experience using statistical computer languages (Python, SQL, R, SAS, etc.) to prepare data for analysis, visualize data, engineer features, and support enterprise-grade analytics solutions
  • 3+ years of experience using cyber security cloud platforms (Google SecOps, AWS, Azure, etc.)
  • 2+ years of experience with SOC threat hunting and incident response
  • Demonstrated expertise leading multiple full life cycle analytics engagements across strategy, design, and implementation
  • Experience leading teams, managing workstreams, and driving delivery quality in a client-facing environment
  • Bachelor’s Degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or related field; or 4 years equivalent professional experience

Nice to have

  • Experience architecting, designing, developing and deploying enterprise data science solutions which include components across the Artificial Intelligence spectrum such as NLP, Chatbots, Virtual Assistants, Computer Vision, and Cognitive Services as well the use of big data tools for the management of massive datasets.
  • Knowledge of the intersection of AI / ML / Advanced Data Engineering and cybersecurity specific use cases for Detection, cyber threat response acceleration.
  • Experience parsing and normalizing cyber or IT specific telemetry datasets
  • Expertise in Python machine and deep learning frameworks and libraries, e.g. PyTorch, Keras, Tensorflow, Scikit-learn, Numpy, SciPy
  • Experience designing and implementing Apache Open Source (Kafka, Storm, Spark) frameworks to process end to end data management life cycle
  • Ability to work independently and manage multiple task assignments.
  • Strong oral and written communication skills, including presentation skills (MS Visio, MS PowerPoint).

What the JD emphasized

  • AI development tools such as vector databases (Pinecone, Elastic, etc.) and AI development frameworks (LangChain, CrewAI, etc.)
  • statistical analysis, machine learning, and data mining techniques
  • cybersecurity cloud platforms
  • SOC threat hunting and incident response

Other signals

  • AI and ML for cyber defense and operations
  • Architect and deploy advanced cyber big data and AI technologies
  • AI-enabled Data Ops capabilities
  • AI and Analytics journey
  • AI development tools such as vector databases (Pinecone, Elastic, etc.) and AI development frameworks (LangChain, CrewAI, etc.)
  • statistical analysis, machine learning, and data mining techniques
  • enterprise data science solutions which include components across the Artificial Intelligence spectrum such as NLP, Chatbots, Virtual Assistants, Computer Vision, and Cognitive Services