This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description MedReview is looking for a talented and experienced Data Scientist to join our dynamic team. As a part of our team, you will leverage your analytical skills and expertise in machine learning to extract insights from complex datasets and drive data-driven decision-making across our organization. You will collaborate closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems. As part of a global team of developers and analysts, the Data Scientist will work with a larger team to design, build, validate, refine, and operationalize models. Responsibilities - Problem Identification: Collaborate with stakeholders to identify business challenges that can be solved through data analysis. - Data Collection & Preparation: Gather data from various sources (SQL databases, APIs, web scraping), then clean and "wrangle" it to ensure accuracy for modeling. - Model Development: Design and implement algorithms and predictive models using machine learning techniques to forecast outcomes or categorize information. - Exploratory Data Analysis (EDA): Analyze datasets to uncover hidden patterns, trends, and anomalies. - Communication & Visualization: Translate technical findings into "data stories" using tools like Tableau or Power BI to influence executive decisions. Qualifications - Master’s degree or bachelor's degree and equivalent experience in a quantitative field (Math, CS, Stats) - Proficiency in Python or R along with SQL for database querying. - Strong foundation in linear algebra, calculus, and statistical modeling. - Experience with frameworks like TensorFlow, PyTorch, or scikit-learn. - Critical thinking, curiosity, and the ability to explain complex concepts to non-technical audiences. - Experience working with global and remote teams.

• Drive the long‑term data strategy for the Rentals Shopping pillar • Elevate statistical rigor, modeling, and experimentation practices across Rentals • Partner with product, engineering, and design leaders to translate complex analysis into clear, actionable product and business strategies • Lead analytical and modeling work across critical problem spaces such as rental search relevance, ranking, personalization, or marketplace efficiency • Design and guide robust A/B tests and other experimentation frameworks • Apply modern AI to increase data science velocity and improve model quality • Coach and mentor data scientists

• Utilize NLP techniques to analyze and process textual data, extract insights, and develop models for various NLP applications, such as sentiment analysis, text classification, and information extraction. • Utilize Time Series Forecasting methodologies to analyze historical data patterns, develop predictive models, and generate accurate forecasts for future trends and patterns. • Collaborate with cross-functional teams to understand business requirements and develop data-driven solutions that address specific challenges and opportunities • Communicate findings and insights to stakeholders through data visualizations, reports, and presentations, and provide recommendations for strategic decision-making in the relevant fields. • Continuously evaluate and improve data collection and analysis processes, ensuring data quality, accuracy, and integrity throughout the data lifecycle • Stay updated with the latest trends and advancements in NLP, Computer Vision, and Time Series Forecasting, and recommend innovative approaches, tools, and techniques for data analysis and modeling in these domains. • Work with the data engineering team to design and implement data pipelines and infrastructure that support data analysis and modeling initiatives.

• Apply advanced analytics and machine learning to broadband access network, service, and subscriber telemetry data. • Work closely with senior data scientists, engineers, and product teams to build models and insights that power network intelligence, service assurance, and subscriber experience analytics within Calix’s cloud platforms. • Analyze and model large-scale broadband telemetry and time-series data used by Calix Cloud. • Develop and validate ML models for Upsell, cross-sell, churn prevention, customer acquisition, anomaly detection, performance forecasting, fault classification, and capacity prediction. • Collaborate with data engineering and platform teams to develop and integrate models into Calix Cloud’s cloud-native analytics pipelines. • Communicate insights clearly to product, engineering, and customer-facing teams via dashboards, reports, and presentations.