AI Data Science Manager

Job Purpose

This is a strategic role for a Data Science professional who will be responsible for building AI/ML models to solve challenges related to optimizing customer experience, enhancing interaction effectiveness, personalizing journeys, and maximizing value from the existing customer base. You will simultaneously design modern customer data measurement systems, creating a solid foundation for data-driven marketing, operations, and product development strategies.

What You'll Do

1. Build Advanced AI/ML Models for Customer-Centric Challenges:

Segment and understand our customers: Develop sophisticated segmentation and clustering models to identify distinct customer groups based on their behavior and value.

Predict and personalize: Build powerful recommendation systems, channel attribution models, and predictive models for churn and conversion likelihood.

Optimize marketing impact: Design and implement solutions to determine the optimal timing, content, channel, and messaging for targeted marketing campaigns.

Automate personalized experiences: Develop automated scenarios for personalized customer care and interactions across various lifecycle stages and touchpoints.

2. Design Robust Customer Data & Measurement Systems:

Establish comprehensive metrics: Create multi-dimensional measurement frameworks (behavioral, attitudinal, transactional, CLTV, etc.) to underpin customer behavior analysis and marketing strategies.

Develop customer scoring models: Design and implement scoring models to assess customer potential, brand loyalty, and campaign responsiveness.

Champion data quality and accessibility: Collaborate closely with BI and data platform teams to standardize data structures, ensuring efficient access, analysis, and connectivity of customer data.

Unlock new data frontiers: Advise on innovative ways to leverage data from our entire customer interaction ecosystem, including CRM, Web/App, Offline, POS, and Customer Service.

3. Drive Practical Applications of GenAI and AI:

Innovate with GenAI: Propose and implement GenAI applications to elevate customer experience (e.g., intelligent chatbots, personalized content generation, automated feedback summaries).

Extract customer intelligence: Integrate LLMs, RAG, or vector search to uncover valuable customer insights from unstructured data sources like emails, feedback, and conversations.

What We're Looking For

Education:

Bachelor's degree or higher in Data Science, Statistics, Computer Science, Econometrics, or a related field with a strong quantitative foundation.

Professional Experience:

5+ years of hands-on Data Science experience, with a strong focus on customer-centric problems, marketing, and user experience.

Proven track record of deploying models such as segmentation, churn/conversion prediction, uplift modeling, product recommendation, multi-touch attribution, and customer journey prediction.

Experience in building customer measurement systems and frameworks is a significant advantage.

A solid understanding of the operational logic behind marketing automation systems, CRM, and DMP/CDP platforms.

Tools & Techniques:

Proficiency in Python, SQL, and popular ML libraries (scikit-learn, XGBoost, LightGBM, TensorFlow, etc.).

Hands-on experience in building data pipelines and deploying models into production.

Familiarity with GenAI architecture, vector databases, LangChain, OpenAI API, or similar technologies is a plus.

Personal Attributes:

Strategic thinker: Understands how customer data impacts business growth and operational efficiency.

Self-starter: Capable of independently driving AI projects from inception to completion, even with limited resources.

Curious and business-minded: Eager to delve into business logic and effectively translate complex technical solutions into understandable insights for non-technical stakeholders.