Data Analyst

Job Description

Job ID: MJ000086

We are seeking a High-Capability Data Analyst who operates with the technical depth of a Data Scientist. You will serve as a key thinking partner for our business and product teams, moving fluidly between high-speed business insights and complex statistical modeling. Unlike a traditional analyst, you will own the end-to-end logicfrom querying raw data to deploying predictive models into production.

Job Description

• Modeling & Scoring: Design, develop, and implement supervised/unsupervised models (e.g., confidence scoring, risk assessment, anomaly detection) to optimize business performance.
• System Integration: Collaborate with Product and Backend Engineering to understand system flows, ensuring that your models and data logic are scalable and implementable in a production environment.
• Advanced Analysis: Perform diagnostic analyses and what-if simulations to solve complex business problems at a quick pace.
• Experimentation: Lead the design and analysis of A/B tests and causal-impact studies to drive product initiatives.
• Data Pipelines: Partner with Data Engineering to design and enrich data pipelines, ensuring high-quality data for both real-time models and business dashboards.
  
  

Job Requirements

• Bachelor/Master's degree in a quantitative field (Statistics, CS, Engineering, Economics, etc.).
• 3+ years of experience in a Data Analyst or Scientist role, with a proven track record of managing multiple projects in a fast-paced environment.
• Expert SQL & Python/R: Proficiency in writing complex, optimized queries and using ML libraries (e.g., scikit-learn, XGBoost) is mandatory.
• Technical Breadth: Strong understanding of Backend (BE) system flows and how data moves through the product lifecycle.
• Analytical Curiosity: Ability to ask clarifying questions and propose multiple methods to solve a problem, weighing pros and cons of each (e.g., accuracy vs. latency).
• AI Productivity: Familiarity with using LLMs (e.g., ChatGPT, Claude) to enhance coding efficiency and research.
• Visualization: Hands-on experience with BI tools (Tableau, Looker, etc.) to communicate findings through storytelling.