Data Scientist – Marketing, Customer & CX Analytics

Analytic Recruiting Inc.; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Analytic Recruiting Inc. is seeking a Data Scientist to support marketing, customer experience, and growth analytics initiatives for a leading financial services organization.

You will build predictive models, dashboards, and pipelines to optimize customer journeys and drive data-driven decisions. The role requires hands-on Python (pandas, numpy, scikit-learn), Power BI, and SQL experience, with strong communication to senior leadership.

Qualifications

• Minimum 3 years of experience in data analytics within financial services.
• Experience in Customer Analytics, CX Analytics, Call Center Analytics, or Growth Analytics.
• Demonstrated experience building predictive models and ML solutions using Python (pandas, numpy, scikit-learn).
• Proficiency with data modeling, data engineering, and analytics tools including Power BI, SQL, and Python.

Responsibilities

• Translate business requirements into analyses, reports, and dashboards for marketing, CX, and growth initiatives.
• Build, validate, and deploy predictive models and ML pipelines to improve customer metrics and operations.
• Analyze customer journeys and call center performance to identify friction points and improvement actions.
• Develop driver analytics to uncover root causes of customer behavior and outcomes.
• Present findings to non-technical stakeholders and senior leadership.

Skills

Data analytics

Python

Pandas

NumPy

Scikit-learn

Power BI

SQL

Customer analytics

CX analytics

Growth analytics

Tools

Power BI

SQL

Tableau

Job description

A leading financial services organization is seeking a Data Scientist to support marketing, customer experience, and growth analytics initiatives. This role blends technical expertise with business acumen to deliver actionable insights, optimize customer journeys, and elevate data capabilities across the enterprise.

Keywords: Financial Services, Data Science, Predictive Models, LLM, Customer Analysis, Call Center Analytics, Sentiment Analysis

Onsite in Florham Park, NJ or NYC offices

Key Responsibilities

• Interpret business requirements and independently conduct analysis, build reports, and develop dashboards to support marketing, customer experience, and strategic initiatives.
• Build, validate, and deploy predictive models, machine learning pipelines, and LLM based solutions to improve customer satisfaction, retention, engagement, and operational performance.
• Analyze customer journeys, call center performance, and CX drivers to identify friction points and recommend improvements that enhance service quality and efficiency.
• Develop driver analytics to uncover root causes of customer behavior, call volume trends, satisfaction scores, and operational outcomes.
• Translate complex analytical findings into clear, compelling narratives for non technical stakeholders and senior leadership.
• Identify and recommend new data capabilities to support strategic goals; collaborate with data enablement teams to implement solutions.
• Engage directly with business partners to understand data needs and respond to ad hoc requests.
• Execute advanced data queries, reconcile datasets, and synthesize results into executive level insights.
• Champion a data driven culture by mentoring analysts and enhancing data literacy across internal teams.

Qualifications

• Minimum 3 years of experience in a data analytics role within financial services, with hands on expertise in largescale data analysis and insight generation.
• Experience in Customer Analytics, CX Analytics, Call Center Analytics, Driver Analytics, or Growth Analytics within financial services.
• Demonstrated experience building predictive models and machine learning solutions using Python (pandas, numpy, scikit learn).
• Proficiency in data modeling, data engineering, and analytics tools including Power BI, SQL, and Python.
• Experience developing reports and dashboards in Power BI or Tableau.
• Strong communication, organizational, and interpersonal skills, with the ability to manage multiple priorities.
• Proven ability to extract key insights and present findings to business audiences.