As the Chief Product Officer (CPO) for a startup that provides pediatric answers 24/7 through WhatsApp, I am responsible for driving the product strategy, website design, and data analysis to improve the user experience for our customers.In this role, I work closely with the product development team to identify and prioritize key features that will enhance the user experience, as well as the IT team to ensure the smooth operation of our technology stack.Additionally, I am responsible for data analysis and interpretation, leveraging insights to optimize our product and service offerings. This involves identifying key performance metrics, conducting data analyses, and translating insights into actionable recommendations for product improvements.Overall, my work as a CPO has enabled me to develop a broad range of skills, from product design and development to data analysis and team leadership. I am passionate about driving meaningful improvements in the healthcare space and leveraging technology to make a difference in people's lives.

As a member of Docokids, I had the unique opportunity to participate in the prestigious Techstars Miami accelerator program. Docokids was selected from a highly competitive pool of applicants to be part of the program, which provided Docokids with mentorship, resources, and funding to help us grow and scale our business.During the program, we received hands-on guidance from industry experts and successful entrepreneurs, who helped us refine our business strategy, identify key growth opportunities, and navigate the challenges of building a successful startup. We also had the opportunity to connect with a network of investors, potential customers, and other entrepreneurs, which helped us to build valuable relationships and expand our reach.Overall, the experience of being part of a startup selected to participate in Techstars Miami was incredibly rewarding and valuable. It provided me with the skills, knowledge, and connections needed to help our company succeed and grow, and allowed me to gain insights into the wider startup ecosystem. I am proud to have been part of such a dynamic and innovative community, and look forward to applying what I learned to future ventures.

I took a career break to focus on my growing family. During this time, I welcomed my newborn child into the world and devoted my time and attention to caring for my family.While my career break allowed me to prioritize my family, I also continued to stay informed and engaged with the healthcare industry. I stayed up-to-date with industry news, research and advancements, and took online courses to further develop my skills.As my child has grown, I decided to return to the workforce, bringing with me a renewed sense of passion and dedication to the field.

As a Senior Data Analyst at HSS, I worked with the analytics group to implement and create a data warehouse and data lake of the clinical data available at the hospital, including research programs, EMR data (Epic), and others.My responsibilities included validating clinical data taken from the EMR and standardizing it in the data warehouse using SQL, Python, and R. I also generated visualizations and reports of observation data using R and performed different analyses to find patterns in different cohorts of patients.In addition, I used PROMs data to evaluate its impact in predicting surgical outcomes. I implemented different machine learning methods in clinical data and insurance data using AWS SageMaker to create predictive analyses for different clinical outcomes as well as management issues.Through my work, I was able to provide valuable insights to clinicians and hospital administrators, helping to improve patient outcomes and operational efficiencies. I am proud of the contributions I made during my time at HSS and continue to be passionate about the use of data and analytics in healthcare.

During the time of developing the capstone project to finish the Masters in Data Science and Biostatistics, I was responsible for a range of tasks related to data cleaning and analysis of insurance claims data for patients with diagnosis of osteoarthritis that had total knee arthroplasty (TKA) or total hip arthroplasty (THA) to evaluate the risk of readmission after major orthopedic surgery.My duties included cleaning the insurance claims data, understanding different diagnosis codes such as ICD10-ICD9-CPT- HCPC as well as CCS algorithm for grouping diagnosis codes. I was also involved in developing predictive models and diagnostic frameworks for more than 250 disease and diagnosis codes using techniques such as logistic regression analysis, random forest analysis, and KNN modeling.Through my work, I gained valuable experience in applying statistical and machine learning analysis for predictive outcomes of readmission. I was able to apply my knowledge of SAS and R to analyze large datasets and identify significant predictors of readmission risk.Overall, my experience on this project was instrumental in developing my technical skills in data cleaning, predictive modeling, and statistical analysis. It also gave me the opportunity to work collaboratively with other data scientists and biostatisticians, and to contribute to important research aimed at improving patient outcomes after major orthopedic surgery.

After completing medical school and starting an orthopedic residency, I realized that this was not the right career path for me. I decided to take some time off to reflect on my interests and passions, and figure out the next step.During this career break, I began teaching myself coding and programming skills, which sparked a new interest in the intersection of healthcare and technology. I started to explore different career paths that would allow me to combine my medical background with my newfound skills in programming and data analysis.Ultimately, I decided to pursue a Masters in Biostatistics and Data Science, which allowed me to gain a deeper understanding of the healthcare industry and the role that data analysis can play in driving meaningful improvements.

As part of my role, I had the opportunity to work closely with different clinical groups in the search to get certified by the Joint Commission International as a Clinical Care Program (CCP) with the JCl. Specifically, I worked with groups focused on diabetes, stroke, joint replacement, neoplasm of the peritoneal, and liver transplant.My responsibilities included creating datasets using redcap and other software for registering patients that were candidates for any of the CCP. This involved working closely with clinical staff to ensure that data was accurately captured and appropriately stored.In addition, I was responsible for analyzing different clinical research results from the CCP, using statistical analysis techniques to identify patterns and trends that could inform improvements in patient care. Through my work, I gained valuable experience in working collaboratively with clinical staff, managing complex datasets, and applying statistical techniques to real-world problems.