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About arenaflex – Pioneering Health‑Focused Innovation

arenaflex is a global leader in the integrated health‑care and retail pharmacy space, serving millions of customers each day through a seamless blend of physical stores and digital platforms. With a heritage spanning more than a century, arenaflex has continuously evolved to meet the changing needs of communities, leveraging cutting‑edge technology to deliver personalized health solutions, convenient pharmacy services, and a robust omnichannel experience. Our mission is to improve lives by making health care more accessible, affordable, and empowering for every individual. As a data‑driven organization, arenaflex invests heavily in advanced analytics, artificial intelligence, and machine learning to transform raw data into actionable insights that shape strategic decisions across the enterprise.

Role Overview – Senior Data Scientist (Remote)

arenaflex is seeking a highly motivated Senior Data Scientist to join our remote analytics team. This role blends sophisticated data science, predictive modeling, and machine learning techniques with real‑world business impact. You will partner with cross‑functional stakeholders—including finance, product, engineering, and senior leadership—to translate complex data sets into clear, data‑driven recommendations that accelerate growth, optimize operations, and enhance the customer experience. While the position is senior‑level, we welcome candidates who are early‑career professionals with a strong foundation and a passion for continuous learning.

Key Responsibilities

• Model Development & Innovation: Design, build, and maintain advanced machine learning models (supervised, unsupervised, and reinforcement learning) using Python, PySpark, TensorFlow, PyTorch, and related libraries. Continuously explore emerging algorithms and methodologies to keep arenaflex at the forefront of analytics innovation.
• Data Engineering Collaboration: Work closely with data engineers to ingest, clean, and transform massive, high‑velocity data sets stored in Snowflake, Azure Data Lake, and Databricks. Ensure data pipelines are reliable, scalable, and production‑ready.
• Business Insight Generation: Translate raw data into meaningful business insights by applying statistical rigor, predictive analytics, customer segmentation, and prescriptive modeling. Communicate findings to non‑technical audiences through compelling visualizations and storytelling.
• Algorithmic Solutions: Develop and deploy algorithms such as decision trees, XGBoost, K‑means clustering, anomaly detection, Bayesian models, and interpretable ML techniques to solve diverse business problems ranging from demand forecasting to fraud detection.
• Experimentation & Optimization: Design, execute, and analyze A/B tests and multivariate experiments to evaluate the impact of new initiatives. Use results to refine models and drive data‑backed product enhancements.
• Cross‑Functional Partnership: Collaborate with product managers, finance analysts, and engineering leads to define data requirements, prioritize projects, and ensure alignment with strategic objectives.
• Technical Leadership: Mentor junior data scientists and analysts, champion best practices in code versioning (GitHub), CI/CD, and agile development, and contribute to the continuous improvement of arenaflex’s analytics culture.
• Strategic Advisory: Provide consultative support to senior leadership on data‑driven decision making, risk assessment, and opportunity identification, helping shape the long‑term roadmap for arenaflex’s digital transformation.

Required Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related STEM field, with at least four years of professional experience in data science, machine learning, or quantitative analysis.
• Demonstrated expertise in building and deploying large‑scale predictive models on cloud platforms (Azure, Databricks) and data warehouses (Snowflake).
• Advanced proficiency in Python, SQL, and PySpark; experience with libraries such as scikit‑learn, TensorFlow, PyTorch, and Matplotlib.
• Strong foundation in statistical modeling, probability theory, and experimental design, with a track record of delivering actionable insights from complex data sets.
• Hands‑on experience with supervised and unsupervised learning techniques, including regression, classification, clustering, dimensionality reduction, and anomaly detection.
• Ability to communicate technical concepts clearly to both technical and non‑technical audiences, translating analytical results into strategic recommendations.
• Proven ab