Data Scientist

About UsJiffy. com launched over a decade ago with a clear mission: to use technology to combine unparalleled customer service with the fastest delivery in the blank apparel industry. Today, our team helps millions of creators, makers, and entrepreneurs bring their ideas to life with quality products and materials to express their craft and grow their businesses, including blank apparel, custom shirts, and DTF transfers. Our focus on providing superior value and customer service remains as strong as ever, and we are continually delighted and inspired by the continued success of our customers.

We are a data-led company that values good people, forthright communication, ownership, constant evolution, and relentless pursuit of excellence. Job SummaryWe are seeking a highly skilled and experienced Data Scientist to join our growing analytics team. The ideal candidate will possess a deep understanding of statistical modeling, machine learning, and data engineering, with a proven track record of applying these skills to solve complex business problems, particularly within the e-commerce domain. This role requires a leader who can not only build sophisticated models but also mentor junior team members and translate technical insights into actionable strategies for business stakeholders.

Key ResponsibilitiesLead the design, development, and deployment of advanced predictive models, machine learning algorithms, and data-driven solutions to optimize various aspects of our e-commerce operations (e. g. , personalization, recommendation engines, pricing, inventory management, fraud detection, customer lifetime value). Collaborate with product, engineering, and business teams to identify opportunities for data science applications and define project scopes. Perform in-depth exploratory data analysis to uncover trends, patterns, and insights from large, complex datasets across a wide assortment of products. Develop and maintain robust data pipelines and ensure data quality and integrity for modeling initiatives.

Communicate complex analytical findings and recommendations clearly and concisely to both technical and non-technical audiences. Mentor and guide junior data scientists, fostering a culture of continuous learning and innovation within the team. Stay abreast of the latest advancements in data science, machine learning, and e-commerce trends, and evaluate their applicability to our business. ion-making. RequirementsQualificationsMust-HavesEducation: Master's or Ph. D. in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, Operations Research, Engineering, or a related disciplineExperience:

Minimum of 6+ years of progressive experience in data science, with at least 3 years specifically focused on e-commerce, retail, or a similar high-volume consumer-facing industryDemonstrated experience in building and deploying data science models across a large and diverse assortment of productsProven leadership experience, including leading projects and mentoring junior team membersTechnical Proficiency: Expert-level proficiency in Python, including libraries essential for data science (e. g. , scikit-learn, TensorFlow, PyTorch, Keras, Pandas, NumPy, SciPy)Strong command of SQL for data extraction and manipulation from various databasesExtensive experience with machine learning techniques (e. g.

, supervised, unsupervised, reinforcement learning), statistical modeling, hypothesis testing, and experimental design (A/B testing)Analytical Skills: Exceptional problem-solving abilities, with a strong analytical mindset and attention to detail. Ability to translate business problems into quantitative questions and actionable solutionsNice-to-HavesExperience with Marketing Mix Modeling (MMM) or Multi-Touch Attribution (MTA) models for marketing attributionExperience with big data technologies (e. g. , Spark, Hadoop, Flink)Familiarity with cloud platforms (e. g. , AWS, GCP, Azure) and their data science servicesExperience with notebook visualization tools (Hex, Deepnote, Jupyter Notebooks, etc. )Knowledge of causal inference methodsBenefitsWhat we offer:

Opportunities to grow within the companyGenerous compensation and employer paid benefitsAnnual wellness and professional development stipendHigh-caliber and supportive team with proven resultsPerks of getting lots of clothing!