Senior Data Scientist

<p style="text-align: center;"><strong>Senior Data Scientist - Job Description</strong></p> <h3><strong>Who we are</strong></h3> <p>Mico is a company with a clear mission: <strong>to Empower every brand by building lifetime trust through humanlike technology.</strong> This ambitious goal sets the stage for our vision and core values.</p> <p>By 2030, Mico aims to be the Asia No.1 Brand Empowerment Company. This mid-term goal outlines our dedication to becoming the leading force in empowering brands across Asia. To achieve our mission, we identify four key values:</p> <ul> <li><strong>WOW THE CUSTOMER</strong></li> <li><strong>SMART SPEED</strong></li> <li><strong>OPEN MIND</strong></li> <li><strong>ALL FOR ONE</strong></li> </ul> <h3><strong>Job Summary</strong></h3> <p>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.</p> <h3><strong>Key Responsibilities</strong></h3> <ul> <li><strong>KPI Design &amp; Stakeholder Strategy:</strong> 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.</li> <li><strong>Data Engineering &amp; EDA:</strong> Clean, preprocess, and validate large, complex datasets (structured/unstructured). Perform deep-dive Exploratory Data Analysis (EDA) to identify patterns, ensure data integrity, and set the initial strategic direction for analysis.</li> <li><strong>Personalization &amp; Recommendation:</strong> Design and implement recommendation engines to enhance user engagement and brand trust, leveraging both classical and deep learning-based approaches.</li> <li><strong>Iterative Model Development:</strong> Develop and deploy predictive models—including customer behavior prediction, customer lifetime value (CLV), media mix modeling, and time-series forecasting—using Python and PyTorch.</li> <li><strong>Advanced Segmentation:</strong> Lead customer behavioral analysis projects using unsupervised clustering techniques to drive personalized brand empowerment strategies.</li> <li><strong>Continuous Improvement Loops:</strong> 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.</li> <li><strong>Collaborative Engineering &amp; Privacy:</strong> Maintain production-grade code repositories using GitHub, ensuring version control and documentation are integrated into the R&amp;D process while adhering to data privacy and ethical AI practices.</li> <li><strong>Cutting-Edge Research:</strong> 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.</li> </ul> <h3><strong>Required Qualifications</strong></h3> <ul> <li><strong>Education:</strong> Master’s/PhD in Statistics, Computer Science, Econometrics, or related quantitative fields.</li> <li><strong>Experience:</strong> 5+ years in data science, with proven expertise in:</li> <ul> <li><strong>End-to-End Ownership:</strong> Proven experience leading projects from initial data preparation and KPI definition through to delivery of final business impact.</li> <li><strong>Programming:</strong> Expert-level proficiency in Python, SQL, and Spark, along with deep practical knowledge of libraries such as Pandas, Scikit-learn, PyTorch, and PySpark.</li> <li><strong>Modeling &amp; Mathematical Expertise:</strong> Extensive experience in the architecture and implementation of Decision Trees, Regression models, and Deep Learning (including LLMs/NLP).</li> <li><strong>Recommendation Systems:</strong> Deep expertise in building recommendation models, including Collaborative Filtering, Content-Based Filtering, Matrix Factorization, and Neural Collaborative Filtering (NCF).</li> <li><strong>Analytical Methods:</strong> Strong command of Unsupervised Clustering/Segmentation techniques and modern Time-Series Forecasting methodologies.</li> <li><strong>Experimental Methodology:</strong> Rigorous skills in offline evaluation, cross-validation techniques, and iterative hypothesis testing to improve model performance.</li> <li><strong>Cloud Platforms:</strong> Hands-on experience architecting and deploying solutions in Azure, Databricks, Snowflake, or AWS.</li> <li><strong>Development Environment &amp; Version Control:</strong> Advanced proficiency with Linux/Unix environments and VS Code, alongside GitHub/Git for collaborative development, branching strategies, and CI/CD workflows.</li> </ul> </ul> <p><strong>Soft Skills:</strong> Exceptional stakeholder management (translating complex data into simple stories), professional time management, and a relentless problem-solving mindset.</p>