Description
Summary:
Seeking a Data Scientist/Analyst to translate business problems into data solutions, work with cross-functional teams, and deploy models into production environments.
Highlights:
1. Opportunity to translate business problems into analytical solutions
2. Engage with cross-functional stakeholders (Marketing, Product, Operations)
3. Take models from experimentation to production environments
**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