Data Scientist

Position Overview The Data Scientist plays a key role in delivering, maintaining, and evolving our data science solutions for clients. This position blends hands‑on analytics, applied machine learning, and software development in a fast‑paced, client‑facing environment. The primary responsibility is to fit, run, maintain, and configure our suite of data science models and pipelines for clients, while also taking on ad hoc analytical projects and contributing to our shared solution code base when capacity allows. This is a hybrid role—part data scientist as an analyst, part developer, and part researcher. You’ll work closely with internal teams and some of the world’s leading brands to test, refine, and operationalize models that drive meaningful business outcomes. When not actively engaged in client delivery, you’ll contribute to our internal development efforts by improving productized data science tools, frameworks, and automation capabilities. The role offers a unique opportunity to gain broad exposure across the full data science lifecycle—from research and experimentation to deployment, performance monitoring, and ongoing model enhancement. It’s designed for someone eager to deepen both their technical and business acumen, expand their experience across diverse use cases, and prepare for advancement into a Senior Data Scientist position. What You'll Do Here Fit, run, maintain, and contribute to the build of proprietary machine learning models including: Marketing and Media Mix. Performance Forecasting. Price Elasticity. Competitive Pricing. Merchandising Optimization. Audience Segmentation. Lift Studies. Collaborate with Sr. Data Scientists, ML Operations Engineers, and Data Engineers to support the build and validation of enterprise data science solutions. Collaborate with marketing and strategy teams to understand client needs and translate them into data science problems. Design and conduct lift studies to validate hypotheses and measure the impact of our solutions. Create insightful visualizations to communicate findings to both technical and non‑technical stakeholders. Stay up‑to‑date with the latest advancements in machine learning and data science, and propose innovative solutions to improve our offerings. Skills And Experience Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Strong proficiency in Python, with experience using common data science libraries such as scikit‑learn, PyTorch, Pandas, NumPy, and Matplotlib. Experience with SQL. Ability to work independently and as part of a collaborative team. Adaptability and eagerness to learn in a fast‑paced environment. Professional and personal integrity. A detail‑oriented mindset, focused on driving results. Excellent verbal and written communication skills. What We Consider As a Plus Experience with MLOps and leading machine learning algorithms like XGBoost, Neural Networks, Regression Analysis, etc. Experience with cloud platforms (e.g., AWS, GCP, or Azure). Experience with AWS SageMaker. Experience working in MLOps framework and ability to contribute to the pipeline and collaborate closely with MLOps Engineers. Experience with AI and agentic systems is a plus. Seniority Level Entry level Employment Type Full-time Job Function Engineering and Information Technology Industries Advertising Services #J-18808-Ljbffr