Pritesh R. Patel

Bringing proven expertise in building and optimizing innovative end-to-end data science solutions, enabling profitable growth by connecting people, processes, and systems. Versatile and pragmatic with an unwavering commitment and passion for helping businesses improve service, capabilities, and costs and advance their strategic vision.
• Working with internal stakeholders to develop a prioritized list of analytics required to help the organization execute to their global business strategy. Putting in place a governance model to manage these needs and add new ones.
• Implementing monitoring tools to aid the IT team on managing the utility of new analytics as they are developed and consumed by the stakeholder community.
• Currently helping a start-up to implement a data analytics eco-system consisting of an Azure Datalake, Alteryx solution for all data ETL into datalake as well as generation of datasets to allow for consumption into Tableau.
• Provided client a series of prioritization tools to help them utilize their resources to focus on what matters. With these tools, the team can achieve a 95% completion rate on their projects (up from 50%) and allows them to focus on those projects that provide the biggest impact to the company.
• Championed ethical AI / ML solutions to optimize key processes, resulting in 40% efficiency boost.
• Led integration of GenAI tool with QMS provider, accelerating learning and insights for CDMO Client, resulting in a 20% faster data analysis and decision-making.
• Utilizing predictive analytics and statistical model building to optimize inventory levels for medicines and supplies for healthcare systems leading to potential Savings of $750K.

Develop and refine CBM's Data Science strategy in collaboration with cross-functional teams, setting the direction for the organization. Leading the effort to integrate GenAI / LLM within our CRM and QMS systems. Collaborate with stakeholders to identify KPIs and data requirements to support data-driven decision-making.
• Collaborated with executive leadership to establish and maintain robust data governance framework ensuring data accuracy, privacy, and regulatory compliance.
• Transformed enterprise capabilities in data and advanced analytics, leading to 40% increase in operational efficiency and strategic decision-making.
• Spearheaded a comprehensive data strategy resulting in $750K supply chain cost avoidance and streamlined client-focused reporting, reducing turnaround time by 5 days.
• Lead and provide strategic guidance to a team of data scientists, guiding them through advanced modeling and inference tasks
• Designed and executed a centralized data analytics platform, enabling real-time monitoring, actionable insights, and informed business growth; Driving time taken to generate these insights from 2 weeks to 2 days.
• Provided stakeholders with a series of prioritization tools to help them focus on what matters. With these tools, the team is able to achieve a 95% completion rate on their projects (up from 50%) and allow them to measure ROI on their investments and activities.
• Collaborated with the HR team to assess Paylocity data integrity during the transition to Workday. Through meticulous cleanup, successfully reallocated employees to expanding departments, preserving jobs, and optimizing hiring costs.
• Partnered closely with leaders from Sales, Marketing, Revenue Operations, Finance, Engineering, and IT to understand the business strategy and data needs; helping to drive efficiencies where possible.
• Identified 15+ potential AI / ML solution targets, in the areas of Finance, HR (People data), EHS, Quality and Supply Chain; all with a key focus on business objective alignment.
• Utilized insights from various data sources to estimate a $300K reduction in unneeded PO’s, while prioritizing delivery lead times and minimizing potential disruptions in the supply chain.
• Managed relationships with data vendors, ensuring access to key data sources and reducing costs by 15%.

Played a vital role in fulfilling the growing demands of the Quality Assurance organization by streamlining analytics of QMS data. Provide technical leadership in establishing best practices in initiating, planning, and executing Big Data application development including ML algorithms. Built strong relationships with stakeholders, understanding their business challenges and translating them into data solutions. Building and leading onshore and offshore teams as needed.
• Led, mentored, and developed a team of Data Scientists and Data Engineers, boosting new analytics production by 25% through re-balancing work duties, driving faster decision-making and competitive advantage.
• Act as the key liaison between the BI & A team and the Quality organization, fostering effective communication and collaboration at the highest level.
• Implemented an AI-driven analytics platform, reducing FTE hours by 10%. Identified key problem clusters, enabling a cohesive action plan.
• Conducted global workforce analysis using Workday data for the Quality organization, aligning open headcounts with corporate strategies. Informed leadership decisions, resulting in the consolidation of teams in Asia and South America, leading to a cost-saving of $7.5 MM in FTE expenses.
• Directed AI solution implementation to achieve a three-day drop-in complaint resolution time and 80% reduction in nuisance investigations, resulting in heightened customer satisfaction and streamlined operations.
• Led the transformation of enterprise capabilities in data and advanced analytics, saving 65% in preparation time for management reviews.
• Led data scientists to deploy employee experience survey and executing sentiment analysis to judge overall employee satisfaction within the Quality Assurance teams.

Championed a data driven culture while offering statistical expertise for predictive analytics (using ML approaches). Teamed up with stakeholders to understand specific data requirements and align with the objectives of the risk management process.
• Pioneered the creation and administration of the company's inaugural data lake, effectively handling intricate data governance, architecture, and regulatory compliance issues, resulting in optimized data management and regulatory alignment.
• Saved over 300 FTE-hours/month by leading a team of 30+ for the development, validation, and launch of first-generation data lake initiative ($2M). Transformed enterprise capabilities in data and advanced analytics.
• Enhanced risk assessments with advanced analytics, driving automation, resulting in $11M in FTE savings and reducing cycle times from 7 months to 6 weeks

Fostered a data-driven approach to reform the Quality Management System (QMS) by developing key performance indicators (KPIs) as well as leading and coaching a team of SMEs in utilizing Lean Six Sigma methodologies and data analytics. Analyzed Quality System data to answer pertinent questions from stakeholders, allowing them to make quick and informed decisions regarding product placement. Supported a methodical re-design of Allergan’s QMS processes, systems and documentation.
• Developed an ML model to reduce development time by 3 months, leading to an estimated $500K in additional revenue.
• Applied time series analysis to successfully extend shelf-life of key product line from 2 years to 3 years, improving product competitiveness and customer retention.
• Enhanced decision making by 85% through structured/unstructured data analysis, reducing OOS errors and boosting advanced analytics accuracy.
• Improved validation success rate by 30% through variance component analysis, enhancing decision-making with reliable data insights.
• Led the re-design and implementation of Allergan’s Internal Audit program, Escalation program, and Document Management processes utilizing a DMAIC and PDCA approach.
• • Accountable for harmonization and ownership of the Change Control, Deviation Management, Investigations, and CAPA programs within Allergan’s overall QMS system.
• Partnered with Corporate Quality Leaders to develop, implement and monitor Annual and long-term Quality Plans across Allergan’s Global Manufacturing Network.
• • Accountable for the implementation of the Global Quality Metrics Program to help proactively identify improvement opportunities for the QMS
• • Drove the alignment of Allergan’s Trackwise solutions globally ensuring compliance to internal documentation, as well as external requirements.
• • Facilitated complex investigations utilizing a structured approach to root cause analysis and corrective action plan development thereby reducing OOS failures and errors by 85%
• • Interacted with numerous notified bodies and regulatory authorities during inspections and post-inspection follow-ups.
• • Conducted biennial reviews of corporate policies to ensure continued alignment with regulations and industry standards.

Developed and implemented a strategy to implement the use of LSS tools and principles to optimize and streamline all validation processes & procedures. Supported the overall Corporate Validation program with respect to Annual goal setting & reporting and metric collection & reporting.
• Facilitated data collection for process monitoring by leading the $4M deployment of a global MES solution while improving procedural compliance, minimizing release times by five days, and dropping investigation cycle times by three days.
• Decreased testing variability by 20% and elevated yield rates by 10% while developing and analyzing multiple Design of Experiments (DOEs) to bolster in-line testing procedures for pre-filled syringes.
• Redesigned the Validation Maintenance program, by using Risk Management tools and data analysis to yield annual savings of over $1.5 million at two commercial sites
• Implemented series of KPI’s to support Management Reviews and to optimize validation activities across the manufacturing network.
• Managed a global team of cross-functional engineers team in the development and deployment of a global Process Monitoring Quality system, using a DMAIC based approach to the process.
• Steered a global team of quality engineers and QA managers in the creation of a Maturity Model for Amgen Quality Systems.

Managed a team of engineers to deploy a Six Sigma program to align with the divisional OpEx program and the corporate Six Sigma program. Developed and deployed training to Six Sigma champions, Black Belts, and Green Belts.
• Enhanced yields on a filling line from 80% to 95% through the certification of visual inspections utilizing Data Analytics coupled with 6-sigma methodologies.
• Utilized DMAIC process to identify failures in high margin product. Implemented solutions to increase success rate of commercial product from 25% to 95%.
• Preformed measurement system analysis (MSA), increasing the predictability of final product specification from 60% to 95%.
• Prevented market stockouts and maximized yield from 25% to 80% while conducting multivariate data analysis to pinpoint the root cause of product failures.

Completed Six Sigma training and certification, achieving the largest savings in first project ever noted by a Black Belt since the inception of Six Sigma at W.R. Grace.
• Applied DMAIC process & Data Analytics to a manufacturing process, yielding cost savings of over $1million in raw material costs and $300K in workforce reduction and shift balancing.
• Mentored 13 Green Belts and 3 junior Black Belts on a global scale.
• Developed and conducted the Design for Six Sigma (DFSS) courses along with Intro to Six Sigma classes.
• Performed data analysis to assist procurement in making informed 'buy vs. make' decisions regarding intermediates, resulting in annual savings exceeding $100K.

Aided R&D engineers to take conceptual designs and products to market. Provided a vehicle for accelerated product manufacturing by locating contract manufacturers. Worked with external vendors to design and build custom equipment to produce products. Worked closely with EH&S and Six Sigma organizations to streamline manufacturing processes yet maintain environmental and safety standards.
• Conducted FMEA on processes to prevent excessive downtime. Worked with manufacturing team to troubleshoot processes and equipment to minimize downtime.
• Analyzed process and lab data to help support unprecedented efficiency and excellence in operations, boosting yields from 95% to 99.9% in less than 3 months for a resin extrusion operation.