Summary: Seeking a data science professional with strong analytical skills to translate business problems into data-driven solutions and communicate findings to diverse stakeholders. Highlights: 1. Translate business problems into structured data solutions 2. Deploy models into production with an MLOps mindset 3. Generate actionable business insights from data **Core Competencies** * 1–3 years of experience in Data Science, Analytics, or a related quantitative role * Strong ability to translate business problems into structured data problems and analytical solutions * Experience working with cross\-functional stakeholders (e.g., Marketing, Product, Operations) to define KPIs, hypotheses, and success metrics * Demonstrated ability to take models from experimentation to production environments **Technical Skills** * Proficiency in Python * Solid understanding of machine learning fundamentals (supervised and unsupervised learning, model evaluation, feature engineering) * Experience building and validating models such as: Customer segmentation (clustering, behavioral profiling) Churn prediction and retention modeling Propensity modeling and marketing attribution * Experience with SQL and working with structured and semi\-structured data * Familiarity with data visualization and BI tools (e.g., Power BI, Tableau, Looker) * Ability to generate actionable business insights from data, not just models **Production \& Engineering Mindset** * Experience deploying models into production (APIs, batch pipelines, or integration with applications) * Understanding of MLOps fundamentals (model versioning, monitoring, retraining workflows) * Experience with Git and collaborative development workflows * Experience working with cloud environments (AWS, Azure, GCP) is a plus **Business \& Analytical Thinking** * Strong problem\-structuring skills and hypothesis\-driven thinking * Ability to design experiments (A/B testing) and measure marketing impact * Understanding of marketing analytics concepts (CAC, LTV, funnels, cohorts, retention curves) * Ability to clearly communicate findings to both technical and non\-technical stakeholders **Personal Attributes** * Strong ownership mindset and ability to work independently * Curiosity and proactive learning attitude * Detail\-oriented with high standards for data quality and analytical rigor * Strong written and verbal communication skills