**Experienced Full Stack Data Scientist – Advanced Analytics and Machine Learning**

Join arenaflex, a leading healthcare and retail company, in its mission to create more joyful lives through better health. As an Experienced Full Stack Data Scientist, you will play a crucial role in driving business growth and innovation by leveraging advanced analytics and machine learning techniques. **About arenaflex** arenaflex is a global healthcare, pharmacy, and retail leader with a 170-year history of caring for communities. Our purpose is to create more joyful lives through better health. With almost 9,000 retail locations across the United States, Puerto Rico, and the U.S. Virgin Islands, arenaflex is proud to be a community health destination serving nearly 10 million customers every day. Our pharmacists play a vital role in the U.S. healthcare system by providing a wide range of pharmacy and healthcare services, including those that promote equitable access to care for the nation's medically underserved populations. **Job Responsibilities** As an Experienced Full Stack Data Scientist, you will be responsible for: * Building models and equipment using technical expertise in machine learning, statistical modeling, probability and decision theory, and other quantitative techniques. Innovate by adapting to new modeling techniques and procedures. * Understanding the business context behind large datasets and developing significant analytical solutions. * Applying analytical rigor and statistical techniques to analyze large datasets, using advanced statistical techniques such as predictive statistical models, customer profiling, segmentation analysis, survey design, analysis, and data mining. Build recommendations and optimization algorithmic designs, perform data retrieval, complexity analysis, and clinical computing. * Programming using tech stack Python, PySpark, Matplotlib, TensorFlow, PyTorch, etc. * Performing machine learning techniques, and supervised and unsupervised algorithms to build predictive models and prescriptive solutions to support various business use cases. * Building algorithms like decision trees, regression, XGBoost, K means, and anomaly detection. Interpretable ML, Bayesian theory, etc. * Utilizing Cloud Computing on Azure/Databricks, querying in Snowflake. * Utilizing software tools and methodologies GitHub, Continuous integration and delivery, agile methodologies. * Collaborating with finance, researchers, software developers, and business leaders to define product requirements and provide analytical support. * Communicating verbally and in writing to business clients and management teams with varying levels of technical expertise, educating them about our systems, as well as sharing insights and recommendations. **Essential Qualifications** * Bachelor's degree and a minimum of 4 years of experience in data science, machine learning, quantitative or computational skills OR High School/GED and a minimum of 7 years of experience in data science, machine learning, quantitative or computational skills. * M.S. in STEM, PC science, statistics systems, physics, mathematics, statistics, data science, machine learning, or similar. * At least 4 years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models. * Advanced experience in SQL, Python, PySpark or other languages. * Advanced degree talent in exploratory data analysis, feature engineering and selection, detecting patterns, learning distributions, visualizing results, and extracting insights to help businesses make informed data-driven decisions. * Experience using decision trees, and building classifiers. * Experience with supervised machine learning techniques (linear and logistic regression, time series modeling, generalized linear models, decision trees, support vector machines, etc.) and unsupervised machine learning techniques (K means, hierarchical clustering, association rules, principal components). * Experience with Cloud ML systems, distributed computing, data pipelines, cloud data stores, and serving engines. * Experience designing and analyzing A/B experiments. * Advanced degree talent in conveying rigorous technical standards and issues to non-experts. * Experience working in dynamic environments and working with ambiguity, prioritizing needs, and delivering results. * Experience efficiently communicating technical solutions and advocating to data scientists, engineering teams, and business audiences. * At least 2 years of experience contributing to business decisions in the workplace. * At least 2 years of direct management, indirect management, and/or cross-functional team management. * Willing to travel up to/at least 10% of the time for business purposes (within the country and out of the country). **Preferred Qualifications** * Ph.D. in STEM, PC science, statistics systems, physics, mathematics, statistics, data science, machine learning, or similar. * Experience working with IoT, and Edge AI is a plus. * Experience in Reinforcement Learning is a plus. * Experience in Healthcare is a plus. **Benefits** * Company-Paid Life Insurance * Medical, Prescription Drugs, Dental, and Vision * Retirement Savings Plan – 401(k) * Employee Stock Purchase Plan * Paid Time Off (PTO) * Holidays * Paid Parental Leave (PPL) * Transportation Benefit Plan * Employee Store Discount * Voluntary Life & Personal Accident Insurance **Why Join arenaflex?** At arenaflex, we offer a dynamic work environment that fosters innovation, collaboration, and growth. Our team is passionate about creating more joyful lives through better health, and we're committed to making a positive impact in our communities. As a full-time employee, you'll enjoy a comprehensive benefits package, opportunities for professional development, and a competitive salary. **How to Apply** If you're a motivated and experienced data scientist looking to join a leading healthcare and retail company, we encourage you to apply for this exciting opportunity. Please submit your resume and a cover letter explaining why you're the ideal candidate for this role. Apply for this job