Data Scientist, Loyalty Exp
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Key skills for this role
About the Role
Engage clients for analytics projects, identify growth opportunities, lead loyalty management initiatives, and utilize data analytics tools for impactful solutions.
Key Skills for This Role
Full Job Posting
Overview
Roles and Responsibilities:
Key Role
- Client Engagements
- : Will be working with select clients with Retail footprint for Analytics project execution with innovative solution using data Analytics.
• Identifying Growth Opportunities
: Discover potential avenues for client growth through data analytics, technology implementation, and introducing cutting-edge data solutions, including Large Language Models (LLMs).
• Data Engineering Support
: Assist in data engineering projects focused on building data transformation pipelines on cloud platforms.
Analytics Use Case Ideation
- :
- Ideate and develop new analytics use cases and projects for clients.
- Lead the implementation and execution of analytics projects from conception to completion.
- Continuously identify opportunities for improving analytics processes and methodologies.
Client Engagement
- :
- Engage with clients to understand their business needs and propose suitable analytics solutions.
- Build solutions to client requirement thereby achieving business use case objectives.
Growth Of Analytics Practice
- :
- Contribute to the strategic growth and development of the analytics practice.
- Stay updated with industry trends and advancements in data science and analytics.
- Implement best practices and innovative approaches within the analytics team.
Loyalty Management Projects
- :
- Provide leadership and expertise on flagship loyalty management projects with select customers.
- Ensure the successful design, execution, and management of loyalty programs.
- Analyze and interpret loyalty data to provide actionable insights and recommendations.
Expertise
- Proficiency in data analytics tools and platforms (Dataiku, SAS, Python, R, SQL, Tableau, Power BI).
- Strong understanding of data modeling, statistical analysis, and machine learning techniques.
- Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
- Strong analytical and problem-solving skills with the ability to derive insights from complex datasets.
- Excellent leadership and team management skills.
- Strong communication and presentation skills.
- Ability to engage with clients and understand their business requirements.
- Problem-solving mindset with a focus on delivering practical and impactful solutions.
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