Job Description:

We are seeking an experienced Senior Analyst – Financial Services Direct Mail Marketing Analytics professional to join our dynamic team. 

The ideal candidate will possess a strong quantitative background, and the ability to translate business problems into scalable analytical solutions. This individual will work closely with cross-functional and client teams. 

Key Responsibilities

• Design, build, and maintain predictive models for direct mail campaign response rates, conversion, and customer lifetime value
• Perform response analysis, ROI modeling, and attribution to measure campaign effectiveness and contribution to marketing mix
• Develop customer segmentation models to identify optimal audience segments for targeted mail campaigns
• Conduct A/B testing and multivariate analysis to optimize creative, messaging, offers, and targeting strategies
• Develop, implement, and maintain statistical and machine learning models using Python and SQL (Google BigQuery preferred)
• Build simulation and forecasting applications to model campaign performance scenarios and optimize mailing lists
• Create Tableau dashboards and automated reporting to track campaign metrics and KPIs
• Write efficient SQL queries and build data transformation pipelines to prepare customer and campaign data for analysis
• Ensure data quality, harmonization, and compliance across analytical projects per financial services regulations (GLBA, FDIC, TCPA, CAN-SPAM, GDPR)
• Design and maintain data models that support real-time and historical campaign analysis
• Stay current on industry trends in marketing analytics, machine learning, and AI
• Mentor junior analysts and contribute to knowledge sharing initiatives

Required

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Business Analytics, or related field
• 4+ years of experience in analytics, data science, or marketing analytics in financial services or related industry
• Direct experience with direct mail marketing analytics, campaign optimization, or customer acquisition modeling
• Proficiency in SQL (Google BigQuery strongly preferred) and Python
• Advanced knowledge of statistical techniques: regression analysis, segmentation, propensity modeling, and experimental design
• Experience with Tableau or similar data visualization tools
• Strong analytical problem-solving skills and working knowledge of financial services compliance requirements

Preferred

• Experience with financial services products (banking, insurance, credit)
• Familiarity with marketing mix modeling (MMM) or multi-touch attribution
• Background in A/B testing and experimental design
• Knowledge of regulatory requirements (GLBA, TCPA, CAN-SPAM, GDPR)

The annual salary range for this position is $78,000 -$93,338. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law.  

Benefits available with this position include:  

• Medical, vision, and dental insurance, 

• Life insurance,  

• Short-term and long-term disability insurance, 

• 401k, 

• Flexible paid time off, 

• At least 15 paid holidays per year, 

• Paid sick and safe leave, and 

• Paid parental leave. 

 

Dentsu also complies with applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, in accordance with its plans and policies.  For further details regarding Dentsu benefits, please visit www.dentsubenefitsplus.com. 

To begin the application process, please click on the “Apply” button at the top of this job posting. Applications will be reviewed on an ongoing basis, and qualified candidates will be contacted for next steps. 

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Location:

USA - Remote - Maryland

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent

Dentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color, national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. 

  

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