Data Scientist, Marketing

Benefits Start Day 1 for Full-Time Colleagues - No Waiting Period! For more information about our benefits, see below! We are proud to be a member of the Rentokil family of companies, the global leader in Pest Control and other services across more than 90 countries. We pride ourselves on being a trusted partner to many of the world's leading brands and serve consumer and business customers across multiple industries. We are extremely proud of our legacy of excellence and constantly work to fulfill our mission to "protect people, enhance lives, and preserve the planet." No sponsorship or OPT available for this role This role will be responsible to apply their analytical and technical skills to solve real-world business problems. The Data Scientist will work closely with stakeholders to collect, clean, analyze, and interpret data, and contribute to the development and deployment of ML models and data-driven solutions. This role requires a strong foundation in statistical analysis, machine learning concepts, and programming, along with a passion for learning and exploring data. Duties & Responsibilities Assist in the collection, cleaning, and preprocessing of large and complex datasets from various sources. Conduct exploratory data analysis (EDA) to identify patterns, trends, and insights in the data. Apply statistical techniques and machine learning algorithms to build predictive models, perform classification, clustering, and other data analysis tasks. Development and validation of machine learning models (Supervised and Unsupervised), and other categories such as Ensemble Methods, and Time-series models. Collaborate with other data scientists and other team members to define project requirements and objectives. Communicate findings and insights effectively through visualizations, reports, and presentations. Stay up-to-date with the latest advancements in data science, machine learning, and related technologies. Document code, methodologies, and results clearly and concisely. Participate in the deployment and monitoring of data science models and solutions. Contribute to the development of data-driven products and features. Assist in the evaluation of new data sources and technologies. Independently plan and execute work across multiple projects, stakeholders, and functional areas Candidate Requirements Education Bachelor's or Master's degree in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related discipline. Experience 3+ years of relevant experience in data analysis, statistical modeling, or machine learning. Strong understanding of statistical concepts, probability theory, and experimental design. Familiarity with machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction). Proficiency in at least one programming language commonly used in data science (e.g., Python, R). Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy in Python; dplyr, tidyr in R). Familiarity with data visualization libraries (e.g., Matplotlib, Seaborn, Plotly in Python; ggplot2 in R). Basic understanding of database concepts and SQL. Strong analytical and problem-solving skills with the ability to work with imperfect data. Excellent written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences. Ability to work independently and collaboratively within a team environment. A strong desire to learn and grow in the field of data science. Experience with cloud computing platforms (e.g., AWS, Azure, GCP). (preferred) Familiarity with big data technologies (e.g., Spark, Hadoop). (preferred) Experience with version control systems (e.g., Git). (preferred) Knowledge of specific industry domains relevant to the company. (preferred) Experience with deploying machine learning models into production. (preferred) Physical Demands and Working Conditions The physical demands