Jason Sroka Email & Phone Number

Lunenburg, MA, US

Cambridge, MA, US

Palm Beach, Florida, US

• Leading Aidéo’s Data Science and Analytics teams, leveraging AI and machine learning advances to transform the medical coding industry, helping to offset the growing coder shortage:
• Hired to propel Data Science efforts. Introduced significant staffing changes including refreshing core team and augmenting with Analytics and Reporting team members, establishing tailored agile processes across.
• Oversaw modeling enhancements that delivered our first full claim generation automation for medically complete claims, meeting the demanding 95% full claim prediction accuracy as required (and our customers audit!).
• Expanded revenue-generating medical coding domains from one (Radiology) to now four (adding Ambulatory Surgical Centers, Anesthesia, and Evaluation and Management), with over twenty-fold increase in volume
• Delivered >90% response rates with increasing portion fully automated, including features that go beyond medical coding to meet our customers’ varied needs and preferences.
• Developed metrics and reporting demonstrating 50% reduction in manual effort for both external and internal claims coders across multiple medical domains using claim predictions where we couldn’t fully automate.

• Provide boutique consulting on applied ML and strategic challenges, with healthcare applications including:
• Demonstrated to a commercial health product company that noise in their sensor's readings made the algorithm they employed a poor match to quickly predict a final value. Identified a better-suited alternative algorithm.
• Analyzed current applications of home automation technology and developed new service offerings for a telecommunications client to safely and energy efficiently apply this functionality to remote medical monitoring.
• Applied and developed machine learning techniques to detect and recognize speech based on surface electromyographic (sEMG) measurements.
• Analyzed 'forced cough' data and algorithms to assess potential for early identification of COVID infections using Deep Learning models

Boston, Massachusetts, US

• Ran a Data Science Center of Excellence, improving all business functions for this leading Internet of Things (IoT) company, including:
• Defined and oversaw the delivery of a roadmap of metrics, reports, dashboards, and data products to grow high-margin revenue products while supporting internal operations.
• Created dashboards translating operational data on 300K+ deployed sensors and tailored for effective rollouts, monitoring, remediation, and executive oversight tasks.
• Developed and ran predictive models for equipment failure enabling proactive replacement.
• Provided sales engineering capabilities to rapidly prototype data products meeting specific customer needs and securing landmark deals.
• Used modeling to demonstrate how to transform a net loss customer to profitability through a new installation strategy; provided monitoring tools to oversee and validate.

• Launched and grew the analytics team for this IoT startup through acquisition, transitioning them from an e-commerce sensor hardware company to an Industrial Internet of Things (IIoT) leader and acquisition target. Key.
• Recruiting, hiring, developing, and leading a heterogeneous team to work across internal and external deliverables.
• Implementing multiple data warehouses to reduce the complexity and timeline for applying common types of queries needed by the analytics team and other business units to efficiently execute their tasks.
• Led data reviews with customers to demonstrate untapped value in their data, building customer-specific data products and data pipelines to meet their individual business needs, and transitioning multiple instances.
• Enabled effective identification, mitigation, and prevention of operational outages through automated analytics.
• Built a range of data products, including an automated classification system to detect problematic refrigeration units and suggest corrective actions or flag specific units as unsuitable for maintaining viable.

• Developed health monitoring and coaching capabilities to positively impact user health by providing continuous, real-time vital signs monitoring from a wrist-based biosensor.
• Built and led the analytics team as needs evolved from algorithm development to validation to combining biometric data with contextual data sources to generate insights, which increased the users’ awareness and.
• Developed algorithms for estimating physiological vital signs from wearable sensors.
• Organically developed (i.e. hacked together with Matlab, R, scripting, chron jobs,...) a back-end system that automated processing of incoming data from prototype devices, applied the latest versions of algorithms.
• Led initiative to migrate to a cloud-based back-end, scaling multiple orders of magnitude in data volume as well as supporting the various analytics performed on the data. The design incorporated considerations of the.
• Served as a translator from the User Experience team’s vision of product features and capabilities into Research and Development programs through testing and validation.

Cambridge, MA, US

• Worked closely with the bioinformatics team across a range of projects to develop and apply statistical approaches for examining gene transcription data to characterize gene regulation, stratify patients for disease.
• Provided analytics services to a global drug vendor, transforming qualitative regulatory gene control knowledge from the public domain into graphical models of gene control pathways for use in determining.
• Validated models with public domain transcription array data after using R packages to ingest, clean, and adjust data for systematic inter-test and inter-experimental differences.
• Integrated software tools from academic partners to apply the latest research methodologies for finding subtle indicators of regulatory relationships in large-scale data sets.
• Developed capabilities briefing materials for business development efforts after performing systematic reviews of customer and internal projects. Used materials to re-engage a major client and explore new areas of.

• Used a wide range of machine learning techniques to create a virtual coach that helped people adopt behaviors to improve their health and wellness. The “coach” learned from its past interactions to optimize its impact.
• Combining team leadership and hands-on development to drive the creation of the virtual coach’s intelligence, incorporating data analytics tools, and metrics to evaluate individual and population-level impact.
• Assumed QA responsibilities for a disastrous contractor deliverable on customer reporting, then redirected project efforts to produce a clean data warehouse and Tableau for the final representation to drive successful.
• Contributed to numerous proposals, RFP responses, and business development discussions to represent how the current platform met needs or could be extended to deliver desired capabilities.
• Implemented the virtual coach, which delivered user interactions designed by Behavioral Intervention experts, nudging individuals to adopt small behavior changes that cumulatively provide strong positive health and.
• Led data analytics efforts to evaluate how specific coach interactions and product features predict engagement levels and health outcomes based on user characteristics.

US

• Worked with Ab Initio's amazingly scalable and fast software to:
• Develop a solution for a telecom carrier that compares monthly Call Detail Records (CDRs) against the CDRs of carriers terminating their calls, helping to determine which bills to refute and providing all the detailed.
• Prototyped a testing tool to evaluate the implementation of a new database against the analyst-defined requirements. This system checked that the right structure existed (e.g. the right fields in the right tables using.
• Developed an in-house tool for characterizing data held in complex XML documents. This tool parsed XML files into multiple constituent segments, storing these segments in individual files, and then profiling the data.

Issy-les-Moulineaux, Île-de-France, FR

• Headed Orange Labs' efforts in “eHealth” – the application of IT and networking to deliver services in professional and personal health & wellness areas (this group was planned to triple in size in 2010, but the Boston.
• Led an internal consulting group for Orange/France Telecom Group, supporting business units by providing expert advice, designing apps and services, and developing prototypes (to provide tangible demos and assess.
• For example, the team developed a personal health and wellness service prototype for the iPhone (and later ported it to Android) that allowed individuals to identify and track their health goals. We used third-party.
• Developed the concept for a voice microblogging service to assist in disseminating health information to populations with high illiteracy rates, which was appropriate for NGOs addressing crises or trying to increase.
• Managed eight simultaneous projects, creating a track record for successful deliveries on schedule and within budget, helping to secure the organization’s reputation as the internal go-to resource in the eHealth area.
• Documented the full portable mobile health and wellness prototype, identifying technical risks and key tasks to use it as the basis for a deployable service (originally scheduled to deploy at the end of 2010).

• Managed a growing group (30+) of engineers, achieving sales and funding goals while developing core competencies to gain actionable information from large volumes of varied data. This included overseeing a portfolio of.
• Led successful proposals for multiple projects (valued at up to $3M) and contributed to others with a total value of over $20M, creating white papers, proposals, and business development discussions.
• Delivered ground demonstration of a Multi-Source Data Fusion system as Technical and Project Lead from project initiation ($8M scope effort).
• Contributed to accreditation as Capability Maturity Model (CMM) Level 3 by helping define software process, leading one of the pilot projects implementing the process, and successfully undergoing an audit.
• Successfully integrated BAE technologies in the areas of tracking, situational awareness, and intelligence analysis in a multi-contractor system, providing counter-IED capability for research evaluations and flight.
• Exceeded success criteria of DARPA contract for speech recognition based on muscle activity by determining an effective combination of parameterization and machine learning approach, securing three-year follow-on.

• Led a team of Ph.D.-level researchers and junior- to senior-level software engineers. Responsibilities included:
• Oversight on projects involving applications and extensions of AI techniques ranging from Bayes Nets to Expert Systems.
• Oversaw the individual development of the section members as well as the creation of team camaraderie.
• Supported Marketing efforts (e.g. proposal writing, collaboration evaluation) to ensure new and continued funding of projects to support the section and allow for steady growth.
• Interacted with other sections, groups, and divisions, providing an internal resource of knowledge related to probabilistic reasoning systems.
• Developed staff planning to match project needs within and beyond section efforts with the skill sets and career objectives of section personnel in a matrixed organization.

• Performed numerous roles across Data Fusion and applied AI projects, including:
• Design and implementation of a Bayesian Network for use in detecting vehicles whose movements within a battlespace are consistent with the movements of vehicles engaged in Theatre Ballistic Missile (TBM) activities.
• Extension of an internal Bayesian Network software tool (C++) to allow for Multi-topological Dynamic Bayesian Networks (DBNs) to improve the TBM vehicle model described above, along with significant debugging of the.
• Development of a convoy detection algorithm and oversight of its implementation in C++.
• User Interface design to make the TBM and convoy detection algorithms accessible to forward-deployed military personnel.
• Development of an approach to transform Bayes Nets used for classification in the missile defense domain into a predictive form, enabling sensor resource management with extended lookahead horizons.

• Initiated and led Emerging Technologies Group within Iperia, which included:
• Prototyping/validating integrations of new technologies and/or products with Iperia's telephony application platform.
• Serving as a technical resource for Business Development, both to introduce technical understanding of the product into business development discussions and to enable effective communication of industry trends back to.
• Developing demo systems for use at trade shows and as sales tools.
• Monitoring standards relevant to future work.The process I introduced for projects within this group, including short-term assignment of engineers from outside the group to work with core engineers, was designed to.
• Leading the development of a voice-driven Auto Attendant application, using a GUI tool to enable an administrator to configure hours of operation and edit the employee data set, which produced XML descriptions of the.

• Involved in all aspects of design and development for speech-enabled telephony applications, with duties including:
• Application Software Design and Development (C++)
• Specification Writing
• User Interface Design
• Customer Relationship Management
• Demo Development and Support

Implemented Jordan's Hierarchical Mixture of Experts Architecture in C programming language for phoneme probability estimation. Presented work with a spotlight poster at the 1994 Advances in Neural Information Processing Systems (NIPS) conference.

Led an effort to determine if high magnetic fields and electromagnetic pulses involved in Magnetic Resonance Imaging (MRI) would cause hazards for subjects with Cochlear Implants.

Developed an artificial intelligence system for use in real-time monitoring and control of fermentation. Conducted a number of fermentations to create a knowledge base and trained a neural network to classify fermentation states for use by an expert system. Tested the system by running fermentations and introducing various faults. Constructed desktop-scale.

Ph.D, Speech And Hearing Sciences

Bachelor Of Science, Electrical Engineering

Bachelor Of Science, Managerial Science