HiveWatch is empowering organizations to protect their people through intelligent orchestration of their physical security programs.

ABOUT US:

HiveWatch is a tech-forward, inclusive organization fostering the evolution of the physical security industry. We are a diverse team of forward thinkers who empower each other to find creative and collaborative solutions in an industry ripe for modernization. We are passionate about the problems we’re solving for our customers and equally passionate about the company we’re building.  

HiveWatch is our Security Fusion Platform™ that works with existing security systems, enabling users to reduce noise, and add an intelligent orchestration layer to help companies manage their current security programs. You can think of it as the operating system for physical security. Alongside this cloud-based platform is our mobile app, Patrol, that connects field resources (guards) to our customer’s operation centers without the need for expensive radio solutions or cumbersome call sheets. Lastly, HiveWatch’s Swarm is our Virtual Global Security Operations Center (vGSOC). Swarm uses HiveWatch’s own in-house state-of-the-art GSOC and trained team to service organizations with limited security resources, or those looking to make changes/transitions to their existing programs.

As a Lead Data Scientist you will be heavily involved in developing the foundational concepts and algorithms used by HiveWatch.  You will report directly to the executive suite, working closely with leadership/engineering/product to develop a data model, concept/definitions/KPIs, and relevant algorithms for maximizing signal detection and actionable intelligence at scale.

WHAT YOU'LL DO:

• Work with engineering to understand the data requirements and work to develop definitions of events, metrics, KPIs, etc. relevant to business and model performance.
• Work with product to develop appropriate algorithms that are effective, transparent, scalable, and accessible for additive/collaborative model improvement.

As a Lead Data Scientist you will be expected to:

• Manage multiple technical projects including:
• Metric/event definitions
• Data governance for model development
• Various predictive algorithms in development by a small team working closely with product and engineering (e.g. 3-7 folks).
• Manage performance of 2-4 data scientists.  
• Understand and work with the data feeds to create analytical data-models for effective analysis and feature/model development (e.g. event detection of video feeds, sensor feeds etc.)
• Develop simple and advanced algorithms for effective signal detection and actionable intelligence. The most relevant skill sets for our type of algorithmic needs are:
• Advanced statistics and experimental design
• Bayesian statistics
• Signal detection theory  (e.g. criterion, D-prime, etc.) 
• 1-d signal processing (e.g. audio, time-series)
• Control theory (e.g. critic-actor systems, iterative bayesian, kalman filter, SLAM systems, reinforcement learning)

YOU SHOULD APPLY IF:

• You have a Master’s degree or PhD in a highly quantitative field (Computer Science, Machine Learning, Control theory, Statistics, Mathematics, Physics, Economics, etc.)
• 4+ years of experience working on AI/ML programs, projects, or related work
• Hands-on experience with advanced statistics, control theory, signal detection theory, classification, sentiment analysis, survival analysis, time series, ensembles, design of experiments, deep learning and NLP using open-source tools.
• Experience in deploying ML algorithms and advanced modeling solutions on Data Science and ML infrastructures
• Expert knowledge in R/Python/SQL and at least one cloud-based AI/ML platform.  Familiarity with UNIX/LINUX environments and BASH/shell scripting is desired
• Experience working with various cloud systems including AWS Sagemaker, etc. 
• Strong organizational skills with an ability to manage multiple projects at any given time
• Strong verbal and written communication skills.  In particular, be able to convert highly technical concepts and results into easily understood business value proposition

PREFERRED QUALIFICATIONS:

• 2+ years of experience working in the fraud or security industry
• Publications or presentations in recognized ML journals or conferences