As a Data Scientist at Merkle Taiwan, you will play a key role in data-driven, customer-centric solutions to solve complex business issues. You will work closely with cross-functional teams including data engineers, business analysts, CRM experts, and other data scientists to deliver innovative solutions. Your expertise in business intelligence, machine learning algorithms, statistical analysis, and data attribution analysis will be crucial in driving data-driven decision-making processes for our clients. You will also act as a data storyteller, uncovering insights and perspectives from vast amounts of data.
Job Title:
Data Scientist
Job Description:
Responsibilities:
Business Dashboard Design: Create data analysis tools such as dashboards and automated reports for analysts and management to use, enabling our brand clients to make data-driven decisions through customer analysis, operational analysis, and decision support analysis to optimize brand membership management strategies.
Bridging Business and Data Expertise: You will leverage your understanding of data, strategic technical delivery, and data visualization development skills. With your experience in BI tools for creating data visualizations, you are not merely a BI developer, but also an effective and empathetic storyteller who collaborates with senior executives and CRM consultants.
Advanced business data analysis and thinking skills: Have clear business acumen and data analysis thinking, and be able to perform multi-data correlation analysis, testing and marketing attribution. In addition, you should also have the ability to conduct experimental design and effect evaluation analysis.
Data Analysis and Preprocessing: Analyze and preprocess large data sets to extract meaningful insights and identify relevant features for model development. Clean, transform, and standardize data to ensure its quality and consistency.
Machine Learning Model Development: Design, develop, and implement machine learning models and algorithms to address business challenges and enhance performance in areas like marketing, customer analytics, and predictive modeling. Use appropriate frameworks and tools to implement and optimize machine learning models, training them using both supervised and unsupervised learning techniques, and evaluating their performance with statistical metrics and validation techniques.
Collaborative Approach: Work with cross-functional teams, including data engineers, business analysts, and domain experts, to understand business needs and transform them into actionable solutions.
Strong SQL or Programming Skills: Capable of independently handling data to derive valuable insights.
Research and Innovation: Keep abreast of the latest developments in machine learning, data science, and related fields. Continuously explore and evaluate new algorithms, methodologies, and tools to enhance the company's data capabilities and competitive edge.
Documentation and Reporting: Prepare reports and presentations to communicate findings and recommendations to both technical and non-technical stakeholders.
Requirements:
Educational Background: Bachelor's or master's degree in Computer Science, Data Science, Information Management, Statistics, or a related field.
Experience: More than 3 years of practical experience in developing and analyzing data science projects.
Programming Proficiency: Expertise in programming languages such as Python, R, or Java for data manipulation and model implementation.
Machine Learning and Statistics: In-depth understanding of machine learning algorithms and statistical techniques.
Data Analysis and Visualization Skills: Proficient in using BI tools like Tableau, Power BI, Looker, and FineReport for data analysis, visualization, and manipulation.
Machine Learning Frameworks: Experience with popular machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
Big Data Technologies: Familiarity with big data processing technologies like Hadoop, Spark, or SQL.
Problem Solving Skills: Strong problem-solving skills and the ability to translate business requirements into technical solutions.
Communication and Collaboration Skills: Excellent communication and collaboration skills to work effectively with cross-functional teams and stakeholders.
Marketing Analytics Experience: Prior experience in marketing analytics, customer segmentation, or digital advertising is preferred.
Cloud Platform Knowledge: Knowledge of cloud platforms such as AWS, Azure, GCP, and experience with cloud-based machine learning services is a plus.
