Marketing Data Analyst

Job Title: Marketing Data Science - Senior Analyst

Exp: 2+ Yrs

Location: Delhi, India

Mode of Work: Hybrid

About the Company:

We are seeking a highly driven Data Scientist Marketing to join our Client Solutions Team. You will be responsible for extracting valuable insights from data, analyzing marketing performance, and providing data-driven recommendations to optimize marketing campaigns. You will collaborate closely with the Client and organization’s product teams to develop and implement advanced analytical solutions.

Responsibilities:

1. Apply data science methodologies, including customer segmentation, clustering, and predictive modeling, to identify distinct customer groups, and behaviors, and forecast key marketing metrics, guiding personalized marketing efforts.

2.Extract, clean, and integrate data from various sources, including Customer Data Platforms (CDP), Adobe Analytics, Google Analytics, CRM systems, and Salesforce data, to ensure data accuracy and reliability for analysis.

3.Design, execute, and analyze A/B tests to evaluate the effectiveness of marketing strategies, advertisements, and website changes, making data-driven recommendations for improvements.

4.Assist in developing marketing attribution models to accurately measure the impact of various marketing channels and touchpoints on customer conversions and sales.

5.Collaborate cross-functionally with marketing, product development, and IT teams to infuse data science insights into marketing strategies, enabling data-driven decision-making and enhancing customer experiences.

Qualifications:

1.Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field.

2.2-4 years of professional experience as a Data Scientist or Analyst in a marketing environment.

3.Experience in financial services and B2B marketing analytics will be preferred.

4.Proficiency in programming languages such as Python or R.

5.Proficiency in SQL for data extraction and transformation.

6.Strong knowledge of statistical analysis, machine learning techniques, and data visualization tools.

7.Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, scikit-learn).

8.Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.

+.Strong problem-solving skills and attention to detail.

10.Ability to work collaboratively in a cross-functional team environment.