Senior Advisory Data Scientist

Overview

FTI is seeking a highly experienced and strategic Senior Advisory Data Scientist with expertise in predictive modeling, data warehousing/data lake architectures, and data architecture to join our dynamic data science team and contribute to a critical cybersecurity project. In this pivotal role, you will lead the development and deployment of advanced predictive analytics solutions to enhance threat detection, incident response, and overall security posture. Leveraging complex cybersecurity datasets, you will derive actionable insights and drive strategic decision-making. You will serve as a trusted advisor, collaborating with senior leadership, security engineers, and threat intelligence analysts to deliver impactful results that mitigate cyber risks and protect critical assets. This position is located in Huntsville and hybrid.

Why choose FTI?  Our products and technologies are exciting and innovative!  Many of these have come from significant investments via the Small Business Innovative Research (SBIR) culture; they truly empower our customers to feel confident in how their organizations are supported. You will also be joining a team united in a common mission; supporting  U.S. national defense and the federal government. Our culture revolves around the 4C’s: Core Values, Commitment, Compassion, and Charity.   Every day we strive to show our passion for our employees and customers, while showing love to our neighbors in the community.

At FTI, we foster a culture of innovation and excellence. We are committed to pushing the boundaries of data science and providing our clients with cutting-edge analytical capabilities. You will have the opportunity to lead challenging projects that directly contribute to national security and technological advancement.

Responsibilities

• Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets.
• Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
• Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data.
• Generate and test hypotheses and analyze and interpret the results of product experiments.
• Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation.
• Develop and implement NLP models for tasks such as sentiment analysis, text classification, information extraction, and question answering, tailored to the specific needs of the project.
• Design, develop, and fine-tune generative AI models for tasks like text generation, summarization, and dialogue systems, exploring innovative applications within the defense context.
• Collaborate with the R&D team to explore and implement novel AI techniques and algorithms, particularly in the areas of NLP and Generative AI.
• Conduct thorough data preprocessing and feature engineering on large textual datasets, ensuring data quality and suitability for model training.
• Evaluate and optimize model performance, using appropriate metrics and techniques to ensure accuracy and efficiency.
• Contribute to the development of data pipelines and infrastructure for training, deploying, and monitoring NLP and generative AI models.
• Work closely with software developers to integrate AI models into operational systems and applications.
• Conduct research and stay up-to-date with the latest advancements in NLP and generative AI, identifying opportunities for application within the project.
• Present findings and technical recommendations to team members and stakeholders, both verbally and in writing.
• Support the development of technical documentation and contribute to knowledge sharing within the team.
• Participate in technical interchange meetings, analytical update meetings, and program management reviews as required.
• Support the collection and organization of various data types, including but not limited to technical manuals, incident reports, and operational logs.

Education/Qualifications

Required:

• Must be a U.S. Citizen and able to obtain U.S. Department of Defense Secret Clearance.
• Master’s Degree in Computer Science, Data Science, Statistics, Mathematics, Cybersecurity, or a related field with 10 years of relevant professional experience, OR a Bachelor’s Degree in the same fields with 15 years of relevant professional experience.
• Extensive experience in developing and deploying predictive models for applications, such as intrusion detection, anomaly detection, and threat intelligence.
• Deep understanding of data warehousing and data lake architectures, particularly in the context of handling large volumes of cybersecurity data.
• Proven experience in designing and implementing data architectures for large-scale cybersecurity analytics projects.
• Proficiency in Python and relevant data science libraries (e.g., scikit-learn, pandas, NumPy).
• Strong experience with SQL and data manipulation languages.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and their security and data services.
• Excellent problem-solving, analytical, and strategic thinking skills, with a strong focus on cybersecurity.
• Exceptional verbal and written communication skills, with the ability to present complex cybersecurity information to diverse audiences.

Preferred:

• Experience working with security information and event management (SIEM) systems and other cybersecurity tools.
• Experience with big data technologies (e.g., Spark, Hadoop) for processing large cybersecurity datasets.
• Experience with data visualization tools (e.g., Tableau, Power BI) for presenting cybersecurity analytics.
• Experience with MLOps practices in a cybersecurity context.
• Relevant cybersecurity certifications (e.g., CISSP, CISM).
• Advanced Knowledge of threat intelligence platforms and practices.

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