Senior Marketing Data Scientist
Hybrid; San Francisco, CA or New York City, NY
$130k-$145k plus bonus and benefits
For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
This new role will be working with senior data scientists to develop, optimize and implement the marketing strategies for client's small and medium lending business.
Marketing Data Scientists will partner closely with marketing managers and leadership to design, analyze, and optimize marketing strategies that drive member growth and revenue. If you are interested in working with highly quantitative teammates and elevating how data and analytics drives marketing and business decisions, this role is for you.
- Drive the growth of business and member products by developing comprehensive marketing strategies, which includes data analysis, model creation, strategy development, and performance monitoring across all channels.
- Collaborate with marketing managers, channel owners, and external partners to identify and strategize on new opportunities and initiatives.
- Analyze and measure the effectiveness of the marketing strategies, including funnel efficiency (click to convert), CPA (cost per acquisition) and ROI (return on investment), to provide data-driven recommendations and drive informed actions.
- Design, analyze, and interpret experiments (A/B tests, quasi-experiments) to inform marketing and growth decisions.
- Design and validate the complete campaign lifecycle, including process flow, data pipeline, model scoring, and execution, in collaboration with the campaign execution team to ensure timely and accurate campaign selections.
- Define key performance indicators (KPIs), design reporting framework and develop self-service dashboards that provide clear visibility into product and business performance.
- Manage the end-to-end Direct Mail (DM) campaigns, including pre-screened (PS) and invitation-to-apply (ITA) across products. This encompasses identifying the underwriting, marketing and suppression rules, clearly defining the data source and logic, executing the code, validating the result and file ingestion, managing the approval process and tracking the campaign performance.
- Perform deep-dive analyses across funnels, user behavior, monetization, and retention to identify growth and efficiency opportunities.
- Transform business objectives into data-driven, actionable tactics and campaigns that generate immediate results and establish a robust foundation for sustained growth.
- Fulfill partner requests promptly by providing timely analysis, adeptly navigating ambiguity, and focusing on solution-oriented approaches..
- Communicate insights clearly to senior leadership and partners, converting complex data into compelling narratives.
- Bachelor's degree in Computer Science, Math, Physics, Engineering, or a quantitative field required; Master's degree preferred.
- 8+ years of experience in data science/analytics role
- Strong communication skills and comfort working directly with Product and Business leaders
- Direct mail experience . Ability to manage the campaign selection and execution process for the DM campaign.
- Strong programming skills in SQL, Python/R and proficiency in Tableau
- Experience in growth, lifecycle, or funnel optimization problems
- Experience building data pipelines with Airflow, preferably in Snowflake.
- Demonstrated experience with experimentation design, hypothesis testing, and statistical analysis
- Knowledge of statistical modeling or machine learning is a plus.
- Ability to operate effectively in ambiguous, fast-moving product environments
- Ability to thrive in a dynamic, cross-functional environment with keen attention to detail.
- Ability to work independently and as part of a team. You should be able to initiate and drive projects to completion
- Demonstrate strong business acumen and curiosity, with excellent communication and presentation skills, including the ability to present to leadership
- Strong preference for industry experience in financial service and familiarity with banking products and marketing channels.
- Experience with the consumer bureau data (Experian/TU)
- Good to have knowledge of business bureau