Sr Data Scientist - Customer Analytics

About Blend

Blend is a global technology and data consulting organization helping leading enterprises solve complex business challenges through data, AI, and technology. Our teams work closely with clients to build practical, scalable solutions that create measurable business impact.

About the Role

We are looking for aSenior Data Scientist to join a customer analytics engagement. In this role, you will apply machine learning, statistical modeling, and customer analytics to help the client better understandcustomer value, customer behavior, and movement across value segments.

You will work on problems involving customer lifetime value, customer segmentation, value transitions, causal analysis, and early-stage next-best-action recommendations.

This is an evolving engagement, so we are looking for someone who combinesstrong technical data science skills with business judgment, curiosity, and a proactive approach to solving ambiguous problems.

What You'll Do

• Build and applymachine learning models to classify customers into low-, medium-, and high-value segments and estimate transitions between these states.
• DevelopCustomer Lifetime Value (CLV) and customer value models to estimate current and future customer value.
• Analyze customer behavioral and transactional data to identify patterns, drivers, and opportunities to strengthen long-term customer relationships.
• Applycausal modeling, experimentation, and related analytical techniques to understand which customer behaviors or interventions influence customer value.
• Contribute to an initialNext Best Action (NBA) proof of concept to identify strategic opportunities for customer engagement and personalization.
• Develop customer segmentation and behavioral models to identify meaningful customer groups and their characteristics.
• Translate business and marketing questions into practicaldata science and machine learning approaches.
• Perform exploratory data analysis, feature engineering, model development, validation, and interpretation.
• Communicate analytical findings and model outputs clearly to both technical and non-technical stakeholders.
• Collaborate with Data Scientists and Data Engineers to leverage data from aunified customer record.
• Work in an evolving client environment, proactively identifying opportunities, proposing analytical approaches, and adapting to changing business priorities.
• Connect technical analysis to business outcomes and help stakeholders understandwhy the model or analysis matters.

What We're Looking For

Required

• 3+ years of hands-on Data Science / Machine Learning experience.
• Strong programming skills inPython.
• StrongSQL skills and experience working with large datasets.
• Hands-on experience developing and applyingmachine learning models to business problems.
• Strong understanding of:
  • Predictive modeling
  • Feature engineering
  • Model evaluation
  • Statistical analysis
  • Customer/behavioral analytics
• Experience with one or more of:
  • Customer segmentation
  • Customer Lifetime Value / customer value modeling
  • Customer behavior modeling
  • Churn / retention modeling
  • Propensity modeling
  • Causal modeling
  • A/B testing / experimentation
  • Uplift modeling
  • Next Best Action / recommendation approaches
• Ability to translate complex analytical problems into practical solutions and communicate insights clearly.
• Strong business judgment and ability to connect analytical outputs to measurable business outcomes.
• Comfortable working with ambiguity and evolving requirements.
• Strong collaboration and stakeholder management skills.

Preferred Qualifications

• Experience incustomer analytics, marketing analytics, consumer analytics, loyalty, or CRM analytics.
• Experience working withtransactional and behavioral customer data.
• Experience with customer value segmentation or movement between customer segments.
• Experience with causal inference, uplift modeling, experimentation, or treatment-effect analysis.
• Experience with propensity models, personalization, recommendations, or next-best-action frameworks.
• Experience inRetail, CPG, Consumer, E-commerce, Loyalty, or Marketing Analytics.
• Experience with PySpark, Databricks, AWS, Azure, or other cloud/data platforms.
• Experience communicating analytical recommendations to senior business stakeholders.

What Success Looks Like

In this role, success means being able to move beyond simply building models. You will be expected to:

• Understand thebusiness problem behind the analytical request.
• Build models that provide meaningful insight intocustomer value and behavior.
• Identify what causes or contributes to changes in customer value.
• Translate analytical findings intoclear business recommendations.
• Proactively identify opportunities to improve the customer analytics approach.
• Work effectively with Data Scientists, Data Engineers, and client stakeholders as the engagement evolves.

Why Blend

At Blend, you will have the opportunity to work on meaningful, real-world data science problems with leading global organizations. You will collaborate with experienced data scientists, engineers, and business stakeholders while solving problems wheretechnical depth, business thinking, and the ability to operate in ambiguity are equally important.