Joslyn Lim，马来西亚吉隆坡联邦直辖区开发商
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Joslyn Lim

Verified Expert  in Engineering

Data Developer

Location
吉隆坡马来西亚吉隆坡联邦直辖区
Toptal Member Since
September 28, 2022

Joslyn是一位经验丰富的数据从业者，在多个行业拥有丰富的经验, 包括技术咨询和客户服务. 凭借她在应用统计学方面的学术背景和机器学习方面的技能, data analytics, Python, and SQL, Joslyn已经交付了许多对客户产生积极业务影响的项目.

Data ScientistUbuntu 16.04Machine LearningData AnalyticsAnalyticsExploratory Data AnalysisData WranglingPostgreSQLPythonPandasNumPyPython 3Microsoft Power BIAgile Project ManagementMicrosoft FlowBERTPrincipal Component AnalysisPower BIAmazon QuicksightMVPTransfer LearningXGBoostAWS FargateNamed-entity Recognition (NER)Stable Diffusion

Portfolio

Dattel
敏捷，Amazon机器学习，Amazon QuickSight, Flutter， .NET 3...
Kognitiv
Python 3, PostgreSQL, Tableau, Microsoft SQL Server, Bitbucket, Jira, FastAPI...
Stop the Traffik
Amazon SageMaker, Python 3, PyTorch, Docker, IBM Cloud, MongoDB, Programming...

Experience

SQL - 9 yearsDatabases - 8 yearsMachine Learning - 6 yearsStatistics - 6 yearsData Science - 6 yearsPython 3 - 5 yearsAgile Project Management - 3 yearsAzure - 2 years

Availability

Part-time

Preferred Environment

Visual Studio Code (VS Code)， Python 3, SQL

The most amazing...

...我参与的项目是建立一个数据湖, data warehouse, dashboards, 团队成员超过20人，在12个月内完成了4个机器学习用例.

Work Experience

Chief Technology Officer

2023 - PRESENT
Dattel
  • 领导一个使用GPT3的五人团队的广告文案和广告创意生成器的产品开发.5 and stable diffusion. MVP在一个区域营销活动中展示，第一周就带来了大约100次使用.
  • 与GCR人员从零开始构建IT策略和数据治理框架，保护公司资产免受网络威胁.
  • 升级了工程和数据团队的开发周期，以采用CI/CD实践, 结果在第一阶段节省了大约20%的开发时间.
技术:敏捷，Amazon机器学习，Amazon QuickSight, Flutter， .. NET 3，软件架构，产品顾问，市场营销，数字广告，战略，OpenAI

Data Science Manager

2023 - 2023
Kognitiv
  • 使用SQL对ATL和BTL活动进行活动前后分析, Python和R来了解活动的可行性和有效性，这些活动能够在非节日期间实现2-3%的平均提升.
  • 领导分析团队使用Python为区域客户进行数据和机器学习模型迁移的迁移和集成测试, SQL, and X-Ray, 这节省了多达2个FTE(手动测试)的工作量。.
  • 就数据分析方法向内部和外部利益相关者提供建议, campaign A/B testing, 和技术架构来实现理想的结果.
Technologies: Python 3, PostgreSQL, Tableau, Microsoft SQL Server, Bitbucket, Jira, FastAPI, Unit Testing, Data Migration, SQL, Software Architecture

Data Scientist

2023 - 2023
Stop the Traffik
  • 举办用户体验发现研讨会，以确定用户痛点和需求.
  • 开发了一个实体情感模型，利用迁移学习预测商业用户的文章情感.
  • 与客户和其他toptaler合作，使用IBM Cloud将机器学习模型投入生产.
Technologies: Amazon SageMaker, Python 3, PyTorch, Docker, IBM Cloud, MongoDB, Programming, Scikit-learn, Large Language Models (LLMs), OpenAI GPT-4 API, Modeling, Exploratory Data Analysis, EDA, Unstructured Data Analysis, Spreadsheets, APIs, Amazon EC2

数据科学家|欧博体育app下载服务

2023 - 2023
D3 Management LLC
  • 将第三方LMS数据集成到Sharepoint列表和PostgreSQL中，使用api生成洞察, Power Automate, and Airflow.
  • 使用Power automation在PostgreSQL内部构建etl核心数据.
  • 为最终用户创建了Power BI仪表板，以加快获得洞察力和做出明智决策的时间.
Technologies: Microsoft Power BI, SharePoint, Apache Airflow, Microsoft Power Automate, Heroku, PostgreSQL, Learning Management Systems (LMS), BI Reporting, Integration, Programming, Data Cleaning, APIs, Amazon EC2, Software Architecture

Lead Analyst

2021 - 2022
AXA Group
  • 将分析引入数字销售团队，为汽车政策部署留存机器学习模型, digital sales dashboard, 政策福利包优化, 哪一种以较低的损失率提高了年毛保费.
  • 领导使用AWS监控MLOps实践的实施, track, maintain, 并改进现有的或正在生产的机器学习模型，将开发周期从6个月缩短到3个月，并提高透明度和可见性.
  • 与财务和精算团队合作，使用数据湖和报告工具(如SAP Webi)实施国际财务报告准则(IFRS) 17，为利益相关者提供及时和细致的见解.
  • 通过策划学习项目，领导整个企业的数据素养计划, assessment, mentoring programs, hiring, retention, 各种参与活动将整体数据素养指数从33提升到50(总分100).
Technologies: Python 3, Redshift, SQL, AWS Glue, SAP Business Intelligence (BI), Databases, GitHub, Microsoft Flow, Microsoft Power BI, SharePoint 365, Python, Data Analysis, Amazon Web Services (AWS), Amazon Machine Learning, Amazon S3 (AWS S3), Project Management, Analytics, Business Analysis, ETL, Excel 365, SharePoint, Pandas, NumPy, Data Wrangling, Jupiter, Machine Learning Operations (MLOps), Amazon SageMaker, Dashboards, Business Intelligence (BI), Amazon QuickSight, Data Pipelines, Regression, Classification, Linux, XGBoost, Data Scientist, Reports, Data Reporting, Cloud, AWS Fargate, Excel 2010, BI Reporting, Integration, Programming, Scikit-learn, Modeling, Exploratory Data Analysis, EDA, Consumer Behavior, Data Cleaning, Large Data Sets, Data Gathering, Amazon EC2

Data Science Manager

2019 - 2021
EY
  • 与区域DnA团队一起领导、管理并赢得了超过100万美元的数据分析项目.
  • 领导并启动了多个分析项目, including attrition modeling, language modeling, optimization, and dashboards, 2到10人的团队为社会和组织带来积极的经济影响.
  • 负责区域团队的人员管理，并负责建立和维持学习计划, events, 并提供指导，以支持团队的持续个人和职业发展.
Technologies: Python 3, Spark ML, Spark SQL, Azure Databricks, Azure, Microsoft Power BI, Tableau, IT Consulting, Agile Project Management, Ubuntu 16.04, R, Jupyter Notebook, Python, Data Analysis, Data Visualization, Project Management, Analytics, Business Analysis, ETL, Pandas, NumPy, Data Wrangling, Jupiter, Data Engineering, Web Scraping, Dashboards, Business Intelligence (BI), Big Data, Data Pipelines, Artificial Neural Networks (ANN), Regression, Deep Learning, Classification, Neural Networks, Keras, Linux, XGBoost, Data Scraping, Data Scientist, Reports, Heatmaps, Cloud, Text Classification, Excel 2010, BI Reporting, Integration, Programming, User Interface (UI), Scikit-learn, Modeling, Exploratory Data Analysis, EDA, Data Cleaning, Large Data Sets, Unstructured Data Analysis, Data Gathering, Spreadsheets, Azure Machine Learning, TensorFlow, APIs, Amazon EC2, BERT, Custom BERT, Software Architecture, Strategy, Large Language Models (LLMs)

Senior Associate – Data Science

2018 - 2019
EY
  • 使用集成模型(XGBoost with Random Forests)为炼油厂开发了一种机器学习优化模型，估计可节省高达100美元,000 for regional factories.
  • 为一家公用事业公司创建了一个使用文本分析的社交倾听仪表板，通过对社交媒体平台上的负面情绪进行及时回应，提高数字声誉评分(DRS).
  • 使用迁移学习为智能城市原型构建了人脸识别和跟踪MVP，用于入侵者检测.
Technologies: Python 3, R, Brandwatch, Microsoft Power BI, RStudio, Python, Data Analysis, Data Extraction, Analytics, Business Analysis, Pandas, NumPy, Data Wrangling, Jupiter, Web Scraping, Dashboards, Business Intelligence (BI), Artificial Neural Networks (ANN), Regression, Deep Learning, Classification, Neural Networks, Keras, Linux, XGBoost, Data Scraping, Data Scientist, Reports, Heatmaps, Cloud, Excel 2010, BI Reporting, Programming, Scikit-learn, Modeling, Exploratory Data Analysis, EDA, Data Cleaning, Data Gathering, Amazon EC2

Head of Research and Analytics

2016 - 2018
Dattel
  • 领导双向职能，用分析术语向跨业务线和职能领域的关键对手表达业务战略, such as software engineering, marketing, etc.在True Vox Asia和Dattel合并之后.
  • Designed, managed, and delivered data experiments, collections, 并在消费者智能平台上提供分析服务，作为中小型企业产品的一部分.
  • Managed hands-on multiple projects, including customer segmentation, brand advocacy, psychometric profiling, 和社会经济研究出版物，使战略形成为消费品牌收购, engage and retain their customers.
Technologies: Python 3, PostgreSQL, Agile Project Management, SQL, R, Git, Design Thinking, Python, Analytics, Pandas, NumPy, Data Wrangling, Jupiter, A/B Testing, Product Development, Regression, Linux, XGBoost, Data Scientist, Heatmaps, Excel 2010, Programming, Modeling, Exploratory Data Analysis, EDA, Consumer Behavior, Data Cleaning, Data Gathering, Product Consultant, Marketing, Digital Advertising, Strategy

汽车索赔零件价格预测模型

基于机器学习回归模型的电机备件价格估算方法, 加快理赔处理时间, 并将零部件价格评估程序系统化. 与业务用户和AWS团队协作, I started from a user persona, process understanding, and brainstorming session. 该团队设计了一个解决方案，将机器学习与运行在AWS架构上的web应用程序结合起来，为不同汽车品牌和型号的备件推荐预测价格. 最后使用的模型是集合梯度增强树(GBT)回归器. 这一举措预计将提高客户满意度，因为它还缩短了索赔处理时间，减少了通货膨胀对备件成本的影响.

保险单的客户保留模型

一种分类机器学习模型，预测哪些政策可能会在即将到来的更新周期中停止. 区域零售一般保险竞争十分激烈, 所以必须监控流失率，并在需要时保留现有客户. 开发团队与业务用户合作，了解在客户流失预测中有用的基本特性. 作为数据科学家团队的一员，我用过去几年的数据来支持这些说法. 该团队建立了一个随机森林(RF)模型，以帮助最终用户保持中立.e.通过奖励或有针对性的促销来吸引冷漠的客户和可能流失的客户.

自然语言处理与建模

该项目旨在预测命名实体, 文档情感和实体情感, locality, and emotion with higher accuracy. 在2019-2020年，Bert是NLP最先进的(SoTA). 尽管如此，东盟语言(如英语和英语)的结果并不令人满意.g.印尼人、东盟华人、马来人等.)，因为底层模型主要使用的是美国语料库. 该团队的目标是在东盟语言方面击败SoTA. From data collection, curation, annotation, QA, data cleaning, model training, evaluation, and testing, 10人的团队为我们的客户提供端到端的交付服务. 我是其中一个语言支柱的所有者，同时也帮助其他语言支柱理解区域语言的上下文. 该团队进行了多次机器学习实验，发现变压器模型对一些语言语料库和它们的混合物效果最好, 因此，将大嵌入技术应用于多语言模型. 作为最终交付物，团队使用Docker将模型和Python管道容器化. 这些模型以0分左右的成绩击败了SoTA.7 F1 score.

Employee Retention Prediction

一个区域外包和共享服务在过去一年经历了很高的员工流失率，希望减少人员流失, especially for the higher performer. 一个由五人组成的团队进行了定性和定量分析，以了解员工的痛点，并向客户提出了解决方案. 我作为一名数据科学家，利用员工的出勤率和离职率进行探索性分析, appraisal and performance, bonus and pay, 以及使用Python从面试过程中提取关键字, R, and Power BI. 然后，将这些见解与流失数据相匹配，通过分类算法预测流失可能性，并总结(聚类和PCA)流失因素，以便客户能够优先考虑并针对影响较大的流失因素采取行动.
2014 - 2016

Master's Degree in Statistics

马来西亚吉隆坡马来亚大学

2008 - 2011

Bachelor's Degree in Mathematics

马来西亚理科大学-马来西亚槟城

MARCH 2023 - MARCH 2026

AWS Certified Machine Learning

AWS

MAY 2022 - PRESENT

企业设计思维的共同创造者

IBM

DECEMBER 2021 - JANUARY 2024

电源平台解决方案架构师专家

Microsoft

SEPTEMBER 2021 - SEPTEMBER 2023

电力平台功能顾问助理

Microsoft

JULY 2021 - JULY 2023

谷歌云认证专业-机器学习工程师

Google Cloud

JULY 2021 - JULY 2023

GCP Professional Cloud Architect

GCP

JANUARY 2021 - JANUARY 2024

Azure AI Engineer Associate

Microsoft

DECEMBER 2020 - DECEMBER 2023

Azure Data Science Associate

Microsoft

AUGUST 2020 - AUGUST 2023

Azure Solution Architect Expert

Microsoft

NOVEMBER 2019 - PRESENT

Professional Scrum Master I

Scrum.org

Libraries/APIs

Pandas, NumPy, Keras, XGBoost, Scikit-learn, Spark ML, PyTorch, TensorFlow

Tools

Microsoft Power BI, Microsoft Flow, Tableau, Git, Amazon SageMaker, Spreadsheets, Azure Machine Learning, AWS Glue, GitHub, Spark SQL, Microsoft Power Apps, Named-entity Recognition (NER), Amazon QuickSight, AWS Fargate, Apache Airflow, Excel 2010, Bitbucket, Jira

Languages

Python 3, Python, SQL, R

Paradigms

Agile Project Management, Data Science, Business Intelligence (BI), Design Thinking, Agile, ETL, Unit Testing

Platforms

Azure, Jupyter Notebook, Microsoft Power Automate, SharePoint 365, Amazon Web Services (AWS), Linux, Amazon EC2, Microsoft Power Platform, Docker, Ubuntu, RStudio, SharePoint, Google Cloud Platform (GCP), Visual Studio Code (VS Code), Heroku

Storage

PostgreSQL，数据库，Amazon S3, Redshift，数据管道，MongoDB, Microsoft SQL Server

Industry Expertise

Project Management, Marketing

Frameworks

Flutter, .NET 3

Other

Ubuntu 16.04, Machine Learning, Data Analytics, Analytics, Data Wrangling, Jupiter, Data Scientist, Modeling, Exploratory Data Analysis, EDA, Statistics, SAP Business Intelligence (BI), IT Consulting, Natural Language Processing (NLP), Data Analysis, Data Visualization, Amazon Machine Learning, Business Analysis, Dashboards, Big Data, A/B Testing, Product Development, Artificial Neural Networks (ANN), Regression, Deep Learning, Classification, Neural Networks, Reports, Heatmaps, Data Reporting, Cloud, Text Classification, Programming, Consumer Behavior, Data Cleaning, Large Data Sets, Unstructured Data Analysis, Data Gathering, APIs, BERT, Custom BERT, Software Architecture, Azure Databricks, Scrum Master, Artificial Intelligence (AI), Solution Design, Solution Architecture, IT Project Management, Communication, Root Cause Analysis, Sentiment Analysis, Classification Algorithms, Principal Component Analysis (PCA), Multivariate Statistical Modeling, Brandwatch, Data Extraction, Cost Reduction & Optimization, Excel 365, Data Engineering, Language Models, Machine Learning Operations (MLOps), Google Cloud ML, Text Analytics, Web Scraping, Data Scraping, GPT, 生成预训练变压器(GPT), Learning Management Systems (LMS), IBM Cloud, BI Reporting, Integration, User Interface (UI), Large Language Models (LLMs), OpenAI GPT-4 API, FastAPI, Data Migration, Product Consultant, Digital Advertising, Strategy, OpenAI, Transformer Models

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