Senior Analyst - Data Scientist Marketing (2-5 yrs)

Job Title: Senior Analyst.

Exp: 2+ Yrs.

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 organizations product teams to develop and implement advanced analytical solutions.

Key Responsibilities:

- 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.

- 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.

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

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

- 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:

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

- 2+ years of professional experience as a Data Scientist or Analyst in a marketing environment.

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

- Proficiency in programming languages such as Python or R.

- Proficiency in SQL for data extraction and transformation.

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

- Experience with data manipulation and analysis libraries (e.

, Pandas, NumPy, scikit-learn).

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

- Strong problem-solving skills and attention to detail.

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

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