[Digital] Analytics Services Data Scientist

Job Description: Digital Analytics Services Data Scientist

Overview

We are seeking a talented Data Scientist to join our dynamic team focused on improving the value of professional services through data science. As part of a diverse team of data scientists from various industries, you will collaborate with in-house experts to solve business problems across different sectors, including fraud detection, customer analysis, demand forecasting, and digital marketing. The role involves employing advanced analytical methods to deliver actionable insights, while also playing the role of a consultant who understands the client’s business process and drives comprehensive solutions from problem identification to future vision.

Key Responsibilities

• Data Analysis & Consultation: Solve business problems by leveraging advanced data science techniques, including statistical analysis and machine learning. You will work with data from various domains like customer behavior, fraud detection, digital marketing, and business forecasting.
• Client Interaction: Serve as both an analyst and a consultant, guiding clients through understanding their business issues and identifying solutions through data insights. Lead interviews, business design, and planning sessions.
• Team Leadership & Project Management: Lead small teams of data scientists, ensuring effective collaboration and delivering high-quality results within defined timelines. Take ownership of the project lifecycle, from issue identification to report creation.
• Research & Development: Stay updated with the latest developments in the field of data science and analytics. Continuously seek ways to enhance the analytical methods and tools used in client projects.
• Industry Experience: Work across a variety of industries (e.g., healthcare, pharmaceuticals, real estate, sports, etc.) to solve industry-specific challenges using data science.

Career Development

• Growth Opportunities: The role offers the potential to develop into a field manager or supervisor, with the opportunity to lead larger teams and projects.
• Professional Development: Access to extensive training resources, including customized learning plans and e-learning courses from global industry leaders. Opportunities for career advancement through hands-on work and leadership experience.
• Work Environment: Flexible work arrangements including a mix of remote work and in-office attendance, depending on project needs. Collaborative and supportive team atmosphere.

Examples of Service Areas

• Marketing Analysis: Analyze real-world data (RWD) for pharmaceutical and medical device manufacturers, helping them understand patient journeys and treatment trends.
• Demand Forecasting: Build predictive models for industries like real estate, such as forecasting office rent fluctuations by analyzing economic indicators and trends.
• Sports Business Analysis: Utilize data to evaluate the business impact of specific initiatives in the sports industry, including monitoring J.League club performance from a business management perspective.

Candidate Requirements

• Analytical Skills: Strong foundation in data analysis, including experience with machine learning, statistics, and data visualization techniques. Proficiency in tools such as Python, R, SAS, SPSS, SQL, or similar.
• Business Acumen: Ability to apply analytical techniques to business problems and deliver strategic solutions based on data insights.
• Consulting Experience: Proven experience in consulting, with a deep understanding of client business processes and the ability to drive business transformations.
• Project Leadership: Experience managing projects, leading teams, and achieving results within defined timeframes and budgets.
• Communication Skills: Strong verbal and written communication skills, able to effectively interact with clients, stakeholders, and team members.

Experience Requirements

• Senior Level: Minimum 5 years of experience in project-based data analysis, including team leadership, system building, and advanced analytics.
• Mid Level: 3+ years of experience with data analysis and project management. Experience with programming languages and building analytical systems.
• Junior Level: 2+ years of experience in data analysis, programming, and system design. Knowledge of data analysis tools and languages is a must.

Additional Information

• Work Hours: Flextime system with standard working hours from 9:30 AM to 5:30 PM.
• Compensation & Benefits: Competitive salary with annual salary reviews, performance-based bonuses, and comprehensive benefits including health insurance, pension plans, and professional development assistance.
• Trial Period: 6 months.
• Restrictions: Concurrent or side jobs are prohibited.

This is a unique opportunity to grow within a forward-thinking team and make a tangible impact by leveraging data science to drive business success for a wide range of clients across various industries.

Requirements

• Data Analysis Expertise:

  • Proficiency in advanced data analysis techniques such as statistical analysis, machine learning, and predictive modeling.
  • Experience working with large datasets and extracting actionable insights from them.

• Programming Languages:

  • Strong skills in programming languages such as Python, R, SAS, SPSS, and SQL for data manipulation and model development.

• Machine Learning & Statistical Techniques:

  • Experience in applying machine learning algorithms (e.g., classification, regression, clustering) to real-world business problems.
  • Knowledge of statistical methods and tools used in data analysis.

• Data Visualization:

  • Proficiency in data visualization tools like Tableau, Qlik, or Power BI to present data insights in an understandable and visually appealing manner.