Senior Data Scientist

Stensul dramatically reduces marketing content creation time - by up to 90% - so teams can better focus on improving marketing performance. Stensul makes this possible by streamlining the collaboration process and simplifying marketing asset creation for all marketers so they can create high-performing campaigns that drive stronger results. Stensul integrates with all leading ESPs/MAPs, workflow platforms, image digital asset management platforms, live content, link tracking, and messaging platforms. Top brands that trust Stensul to solve their most demanding marketing creation problems include BlackRock, Cisco, Demandbase, Equifax, Greenhouse, Siemens, and Thomson Reuters. At Stensul, our top priority is maintaining a people-first, diverse, and inclusive culture. We look for people that live by our core values - Garra, Learning Agile, Above & Beyond, and Team Players. We’re committed to investing in your growth through mentorship, coaching, and meaningful professional development. If you thrive in a fast-paced environment and are eager to take ownership of a large, revenue-generating area of the business, we want to hear from you What you'll do As a Senior Data Scientist, you’ll be a key leader in leveraging our data assets to drive strategic business outcomes, focusing on critical areas like customer behavior, pricing optimization, and business forecasting. You will design, build, and deploy advanced analytical models, including those for churn prediction and customer segmentation. A core part of your role will involve transforming complex model outputs into interactive data applications that enable business users to make self-service, data-driven decisions. You will also explore and apply cutting-edge techniques in NLP and LLMs to extract value from unstructured marketing and customer interaction data. We’re in a period of high growth which means we move fast, but you’ll do so alongside smart, driven individuals in a fun, collaborative environment with opportunities for growth. Learning Agile is one of our core values, which means that we are always identifying ways to make things better, and welcome new tools and languages that help us improve the way we work. Specific responsibilities include: Designing, developing, and validating advanced statistical and machine learning models to solve high-impact business problems, such as churn prediction, customer lifetime value (CLV), and pricing elasticity. Leading customer segmentation and cluster analysis initiatives to identify distinct customer groups and inform Go-to-Market (GTM) strategy and personalization efforts. Building and deploying interactive data applications (e.g., dashboards, prediction interfaces) using tools like Streamlit, Dash, or Gradio to operationalize model insights and enable self-service consumption by business teams. Exploring and experimenting with Natural Language Processing (NLP) and Large Language Models (LLMs) to analyze unstructured data (e.g., support tickets, sales notes, marketing copy) and derive actionable insights. Collaborating with Data Engineers to ensure robust data pipelines and production-ready deployment of models within a stable MLOps framework. Clearly communicating complex analytical findings, model methodologies, and business recommendations to both technical and executive stakeholders. Own and lead end-to-end data science projects from problem definition to final deployment and monitoring in an autonomous way. Proactively adding positive energy to our rapidly growing company. Your skills and experience Advanced Modeling Expertise: Deep experience designing, implementing, and validating predictive models, including specific expertise in churn modeling, pricing optimization, and cluster/segmentation analysis (e.g., K-Means, DBSCAN, hierarchical clustering). Programming & Statistics: Expert proficiency in Python (including packages like Scikit-learn, Pandas, Statsmodels) and SQL . Data Application Development: Proven experience building and deploying interactive data applications or internal tools using frameworks like Streamlit, Dash, or Gradio . NLP/LLMs (Desired): Practical experience with Natural Language Processing techniques (e.g., sentiment analysis, topic modeling, named entity recognition) and familiarity with architectures and use cases of Large Language Models (LLMs) . MLOps and Deployment: Familiarity with model versioning, testing, and deployment processes within an MLOps framework (e.g., using tools like MLflow, Airflow, or Kubeflow). Statistical Rigor & Business Acumen: Strong ability to translate ambiguous business problems into well-defined analytical projects with measurable impact and communicate complex statistical concepts clearly. Autonomous & Collaborative: Comfortable leading complex projects independently while effectively collaborating with Data Engineering, Product, and GTM teams. What we offer Competitive salary & benefits Company laptop and phone reimbursement (if required) Other awesome secret benefits we’ll tell you once you are on the team Being a part of an amazing, inclusive team that lives by our shared values and is committed to building the next phase of stensul Stensul is proud to be an Equal Opportunity Employer building a diverse and inclusive workforce. If your experience is close (even if not a perfect fit) to what we’re looking for, please consider applying. Experience comes in many forms – skills are transferable, and passion goes a long way. We know that diversity makes for the best problem-solving and creative thinking, which is why we’re dedicated to adding new perspectives to the team and encourage everyone to apply. #J-18808-Ljbffr