Senior Data Scientist

Job Title: Senior Data Scientist

About the job

Mico is a company with a clear mission: to Empower every brand by building lifetime trust through humanlike technology. This ambitious goal sets the stage for their vision and core values.

Who we are

By 2030, Mico aims to be the Asia No.1 Brand Empowerment Company. This mid-term goal outlines their dedication to becoming the leading force in empowering brands across Asia.

To achieve their mission and vision, Micoworks identifies four key values that guide their work:

• WOW THE CUSTOMER
• SMART SPEED
• OPEN MIND
• ALL FOR ONE
  
  

Mico's mission, vision, and values paint a picture of a company dedicated to empowering brands, working with agility and open-mindedness, and prioritising customer success.

Job Summary

The Senior Data Scientist will work on data-driven initiatives to solve complex business challenges, leveraging advanced analytics, machine learning, and statistical modeling. This role requires expertise in translating data insights into actionable strategies and collaborating with cross-functional teams. Ideal candidates will have a strong background in analytics, or tech-driven industries.

Key Responsibilities

• KPI Design & Stakeholder Strategy: Partner with cross-functional stakeholders (e.g., Marketing, Finance) to define and propose business KPIs that are logically sound, reasonably challenging, and easily communicable to non-technical teams.
• Data Engineering & EDA: Clean, preprocess, and validate large, complex datasets (structured/unstructured) from multiple sources. Perform deep-dive Exploratory Data Analysis (EDA) to identify patterns, ensure data integrity, and set the initial strategic direction for analysis.
• Iterative Model Development: Develop and deploy predictive models—including customer behavior prediction, customer lifetime value (CLV), media mix modeling, and time-series forecasting, using Python and PyTorch.
• Advanced Segmentation: Lead customer behavioral analysis projects using unsupervised clustering techniques to drive personalized brand empowerment strategies.
• Continuous Improvement Loops: Systematically identify bottlenecks in model accuracy through rigorous evaluation and error analysis; iterate on model architectures and data features to consistently hit and exceed target KPIs.
• Collaborative Engineering & Privacy: Maintain production-grade code repositories using GitHub, ensuring version control and documentation are integrated into the R&D process while adhering to data privacy and ethical AI practices.
• Cutting-Edge Research: Research and implement state-of-the-art techniques, including LLMs/Generative AI, NLP, and Deep Learning, to enhance business strategies and solve brand empowerment challenges.

Required Qualifications

• Education: Master’s/PhD in Statistics, Computer Science, Econometrics, or related quantitative fields.
• Experience: 5+ years in data science, with expertise in:
• End-to-End Ownership: Experience taking a project from initial data preparation and KPI definition through to final business impact.
• Programming: Python, SQL, Spark, and libraries (Pandas, Scikit-learn, Pytorch, and PySpark).
• Modeling & Math: Decision trees, regression, and Deep Learning (including LLMs/NLP).
• Analytical Methods: Unsupervised clustering/segmentation and time-series forecasting.

• Experimental Methodology: Strong skills in offline evaluation, cross-validation techniques, and iterative hypothesis testing to improve model performance.
• Cloud platforms: Azure, Databricks, Snowflake, or AWS.
• Version Control: Proficiency with GitHub/Git for collaborative development, branching strategies, and CI/CD workflows.
• Soft Skills: Exceptional stakeholder management (translating complex data into simple stories), time management, and a relentless problem-solving mindset.