Data Scientist

Key Skills: Pyspark, Python, Data Visualization

Roles and Responsibilities:

• Build and deploy predictive and event-based models to improve marketing effectiveness.
• Lead the use of data science techniques to derive customer insights and drive decision-making.
• Design and develop advanced feature engineering pipelines and feature stores for Marketing use cases.
• Leverage online and offline customer data, digital interactions, and demographics to develop targeted marketing strategies.
• Collaborate with stakeholders including data scientists, engineers, architects, and business teams to deliver impactful data science solutions.
• Deliver insights using advanced data visualization tools and effectively communicate findings to senior stakeholders.
• Continuously explore and implement new analytics methodologies to solve emerging business challenges.
• Promote a culture of data innovation, standardization, and reusability across the Marketing Data Science team.

Skills Required:

• Strong enthusiasm for analytics and data science with a continuous learning mindset.
• Proven experience in solving business problems using machine learning and statistical methods.
• Strategic thinking with a customer-centric focus.
• Excellent problem-solving and documentation skills.
• Strong interpersonal, collaboration, and stakeholder management skills.
• Ability to clearly articulate complex technical concepts to non-technical audiences.
• Proficient in:
  • Python, PySpark, SQL
  • Spark MLlib, Data Science Libraries (e.g., Scikit-learn, XGBoost, etc.)
  • Data visualization tools (e.g., Tableau, Power BI, Plotly, Matplotlib)
  • Cloud platforms (Databricks preferred; AWS, Azure, or GCP acceptable)
  • Source code control using GitHub

Required Experience:

• 15+ years of experience in leading data science or machine learning teams.
• Proven track record of deploying scalable ML models and delivering measurable business outcomes.
• Hands-on experience working with structured, semi-structured, and unstructured data.
• Strong background in customer and marketing data analytics.
• Deep understanding of AI/ML trends and their business applications.
• Experience presenting insights and data-driven recommendations to senior stakeholders.

Desirable Experience:

• Experience with Adobe Analytics or other digital analytics tools.
• Prior work in financial services or customer lifecycle marketing analytics.
• Development and implementation of AI/ML roadmaps.
• Experience driving continuous improvement in data science practice and innovation culture.

Education:

• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or related fields.
• Evidence of ongoing professional development through certifications or short courses in Data Science or AI