Eleana Tan

Eleana Tan

Data Analyst


Goal-oriented Data Analyst with 4 years of experience at Yara International, driving digital transformation in Africa and Asia's agricultural space through data. Skilled in SQL, Python, and BI tools such as Power BI, Metabase, Amplitude, and Looker Studio, as well as marketing analytics platforms like Appsflyer, Clevertap, and MoEngage.

Passionate about leveraging data to create meaningful user value in high-impact industries. Experienced in uncovering actionable insights and optimizing performance across mobile apps and eCommerce platforms through statistical analysis, predictive modeling, and experimentation. Proven ability to support user growth, improve marketing ROI, and guide strategic decisions through data.

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CONTACT

SINGAPORE

+65 92214801

eleanatan.work@gmail.com


EDUCATION

NATIONAL UNIVERSITY OF SINGAPORE

  • Bachelor of Science (2017-2021)
  • Major in Statistics
  • Specialisation in Business & Finance Statistics

CERTIFICATIONS

  • Machine Learning by Stanford University & DeepLearning.AI on Coursera

SKILLS/TOOLS

  • Python, R, SPSS, SQL, VBA
  • Tableau, PowerBI, Metabase, Looker Studio
  • Rudderstack, Appsflyer, Clevertap, Moengage, Amplitude
  • Google Ads, Facebook Ads
  • Teamwork
  • Time Management
  • Effective Communication
  • Critical Thinking

LANGUAGES

  • English (Fluent)
  • Mandarin (Fluent)
  • German (Intermediate)

EXPERIENCE

Yara International

May 2021 - Jul 2025

Data Analyst

  • Built and maintained performance dashboards for Marketing, Product, and Global teams, enabling decisions across distributor, retailer, and farmer channels — helped Africa team prevent $9,000+ in commission leakage by exposing fraudulent promoter claims.

  • Improved data reliability by managing the integration of third-party tools (e.g., Appsflyer, Google Analytics), collaborating with product and engineering teams to ensure accurate in-app event tracking.

  • Led marketing analytics initiatives including customer segmentation, media mix modeling, ROI measurement, and Customer Lifetime Value (CLTV) estimation to optimize campaigns — Identified high value customers for iOS launch targeting, enabling Thailand team to achieve $4.5 Million through in-app transactions in 1 month since launch.

  • Drove product analytics to uncover insights on feature usage, user retention, user satisfaction and funnel performance, informing product roadmap and improving user engagement — Analyzed user behavior on newsfeed feature to identify high-performing content patterns, leading to a 20–30% lift in 7-day retention and influencing roadmap priorities for content delivery.

  • Delivered key business insights through sales trend analysis, anomaly detection, forecasting through supervised learning — Explored sales trigger analysis, Multi-Linear Regression models and XGBoost, improving sales volume forecasting by 40%.

  • Steered annual business planning by providing data-backed forecasts and partnering with cross-functional stakeholders to define and align on performance targets.

Inland Revenue Authority of Singapore (IRAS)

Jan 2021 - May 2021

Tax Analytics Intern

  • Predictive modelling to flag out GST Refund Claims and translation of data preparation script from SAS to Python to use on Databricks

  • Built a Power BI dashboard to monitor the usage of data science/AI solutions for the department

SCOR Reinsurance

Sep 2020 - Dec 2020

Pricing Actuarial Intern

  • Assisted the renewal of reinsurance treaty pricing and the revision of pricing guidelines for the SEA market

  • Conducted statistical analysis on Long Term Disability/Critical Illness portfolios based on clients’ historical accounts and developed new pricing tools for policy riders (Total Permanent Disability and Backdating)

  • Researched and analyzed national statistics for actuarial studies on accelerated Critical Illness in older ages


GITHUB PROJECTS

Sales & Marketing Ecommerce Tableau Dashboard

  • Analyzing the transaction and marketing data of a Brazilian ecommerce platform from 2016 to 2018 in SQL, Python and Tableau

Frequent Pattern Mining for Product Recommendations

  • Applying frequent pattern mining techniques to optimize marketing strategies, enhance product bundling, and improve the overall shopping experience