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Data Scientist, Customer

Full Time
Science & Technology
4 months ago
Job Description

OVERVIEW

The Data Scientist, Customer Experience Operations (CXO) will lead the company’s data analytics efforts to collect, process, analyze, and report data, and provide deep insights into customer behaviors, trends, and interactions across all resort touchpoints from its multiple properties. This role involves applying data science techniques to segment customers, develop predictive models, and recommend data-driven strategies to optimize customer satisfaction and loyalty. The Data Scientist, CXO will collaborate closely with the Customer Experience Managers (CXMs; Prestige, Premier, Prime) and work with cross-functional teams, utilizing AI, machine learning, and other advanced analytics methods to support the integrated resort’s strategic customer experience goals. The Data Scientist, CXO will be a key player in transforming raw data into actionable insights that drive decision-making, improve operational efficiency, and elevate customer experiences. As the intelligence center for the CX team, this role will also involve documenting data processes and ensuring data integrity and accuracy. The Data Scientist holds a Manager position and will oversee a Junior Analyst, ensuring the efficient operation of the unit’s data center and analytics function.

 

KEY RESPONSIBILITIES

1. Data Collection and Processing
a. Lead the collection, cleaning, processing, and analysis of data related to customer experience across all business units and diverse sources (e.g. customer feedback, transactional data, CRM systems, etc.).
b. Design and maintain data pipelines that support real-time analytics and reporting.
c. Ensure data quality and integrity by developing and maintaining data collection systems, processes, and protocols for continuous data validation.
d. Oversee data warehousing and ensure that data is stored securely and efficiently for easy access and analysis.

2. Data Analytics and Modeling
a. Use advanced statistical models, machine learning, and AI to analyze customer data to identify trends, patterns, and insights that can drive improvements in customer experience.
b. Create predictive models for customer segmentation, churn prediction, and lifetime value estimation.
c. Track real-time customer interactions and provide recommendations for operational enhancements. 
d. Develop and deliver regular reports on key performance indicators (KPIs) to the CX VP, CXO Director, and other stakeholders.
e. Provide data-driven recommendations to the CXMs to support their strategic initiatives.

3. Customer Segmentation & Personalization
a. Based on data segmentation, lead efforts to create detailed customer profiles, targeting high-value customers with personalized experiences.
b. Utilize clustering, classification, and other machine learning techniques to identify hidden patterns and create actionable customer segments.

4. Data Reporting and Visualization
a. Design and develop interactive dashboards and visual reports (using tools like Tableau, Power BI, or similar platforms) to present insights to stakeholders.
b. Translate complex data analysis into clear, actionable recommendations for non-technical audiences, ensuring that all stakeholders understand key insights.
c. Regularly report on key performance indicators (KPIs) related to customer satisfaction, loyalty, and operational efficiency.

5. Collaboration and Communication
a. Collaborate with IT to manage data warehousing solutions and ensure the seamless integration of analytics platforms.
b. Work closely with the company’s operational teams (Gaming, Resort, G&A) via the CXMs to ensure that data insights are aligned with the company’s customer experience objectives and effectively used to improve customer engagement, such as developing personalized customer moments, journeys, and campaigns.
c. Work closely with the Junior Analyst to ensure the timely and accurate completion of data-related tasks.
d. Serve as the primary point of contact for all data science projects, providing leadership in the interpretation and use of data.

6. Documentation and Process Management
a. Document data collection methods, processes, and protocols to ensure consistency and reliability.
b. Develop and maintain a comprehensive data dictionary and metadata documentation.
c. Ensure that all data processes comply with relevant data protection regulations and industry best practices.

7. Continuous Improvement & Innovation
a. Stay up-to-date with the latest data science trends and emerging technologies to continually improve the company’s data analytics capabilities.
b. Propose and implement innovative strategies for using AI and machine learning to optimize operations and enhance the customer journey.
c. Lead workshops and training sessions to foster a data-driven culture across the organization.

8. Team Leadership, Mentorship, and Development
a. Lead and mentor the Junior Analyst, providing guidance and support on analytical projects and safeguard alignment with business goals to ensure high performance.
b. Conduct regular training sessions to enhance the data analysis skills of the team, promoting continuous improvement of the team’s data science skills by stimulating learning and upskilling initiatives.
c. Foster a positive work environment that encourages continuous learning and data-driven decision-making.

 

QUALIFICATIONS
1. Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field.
2. 5-7 years of experience in data science or advanced analytics roles, preferably within the hospitality or customer experience sector.
3. Strong technical proficiency:
a. Expertise in programming languages like Python, R, and SQL.
b. Strong experience with data visualization tools (e.g., Tableau, Power BI).
c. Proficient in machine learning libraries (e.g., scikit-learn, TensorFlow) and big data technologies (e.g., Hadoop, Spark).
4. Excellent analytical and problem-solving skills, with the ability to translate data into actionable insights.
5. Strong background in statistical analysis, predictive modeling, and data mining.
6. Strong leadership and team management skills, with experience leading data analytics teams.
7. Excellent communication skills, with the ability to present complex data in a clear and concise manner.
8. Familiarity with hospitality and customer experience management best practices, focusing on customer retention, personalization, and satisfaction, as well as data protection regulations and industry best practices.

Specialization:

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