Converse Data and Analytics builds analytic-based solutions to manage the marketplace and optimize the supply chain. Using big data, advanced analytics and innovative technology, the team strives to ensure that Converse gets the right product to the right place at the right time for the consumers. The Senior Data Scientist will focus on Converse’s overall growth over the next several years by using predictive analytics, enhancing decision making and driving to action against strategic priorities.
Requirements
- Advanced proficiency in Python for data analysis, statistical modeling, and machine learning, with hands-on experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, or PyTorch.
- Expertise in building, training, scoring, tuning, and deploying predictive models at enterprise scale, with a strong understanding of model lifecycle management in production environments.
- Experience with modern data platforms including Snowflake for scalable data warehousing and Databricks for collaborative data science and machine learning workflows.
- Proven ability to design and implement statistical and machine learning models to solve complex business problems, including regression, classification, clustering, and time-series forecasting.
- Familiarity with mainstream tools and packages across the Data Science/Analytics lifecycle, including model versioning, experiment tracking (e.g., MLflow), and automated model retraining pipelines.
- Strong understanding of data engineering principles, enabling seamless collaboration with engineering teams to ensure robust data pipelines and model integration.
- An ability to communicate insights and model outcomes effectively to technical and non-technical stakeholders, driving data-informed decision-making.
Responsibilities
- Join a team that is responsible for building models that uncover insights consumer preferences for products to inform Converse’s business teams and organizations.
- Develop new sophisticated algorithms and improve existing approaches based on statistical/econometric methods, machine learning techniques and big data solutions to forecast
- Work closely across different businesses to answer key questions about how to design the best products, line plans, and assortments to serve athletes and consumer experience.
- Ideate, develop, and operationalize algorithmic solutions for bringing a consumer lens to key decisions facing Product Creation, Merchandishing, different planning, Operations, and consumer teams.
- Stay up to date on relevant industry trends and pull from your generalist data scientist toolkit to identify the right data science approach to each problem you encounter.
- Support the adoption of analytic products through effective storytelling and collaboration with key partners.
- Participate in a continuous learning environment within the analytics community through persistent development of new skills and sharing of knowledge through mentorships and contributions to the open-source community.
Other
- Dependable teammate with strong hands-on analytics experience, drive, and curiosity.
- Know how to rise above the numbers and explain the crucial insights to users at all levels.
- Simplify and distill business complexity into testable hypotheses and scalable solutions.
- Ask good questions, are continually learning as well as finding opportunities to share knowledge with others!
- A passion for continuous learning and staying current with emerging trends in data science, machine learning, and AI.
