Data Science Manager - Customer & Marketing

Bachelor of Science (Computers), MBA/PG Diploma in Business Mgmt (Marketing)

Nationality: Any Nationality

Vacancy: 1 Vacancy

Job Description:

We are seeking a talented Data Science Manager to join our team. This role is pivotal in executing customer-focused data science projects to enhance marketing effectiveness and customer experience using advanced analytics and machine learning techniques.

What you will do:

• Implement various predictive models such as lead scoring, conversion prediction, customer segmentation, churn prediction, and next best action/offer recommendations.
• Create marketing and customer KPI metrics using statistical techniques and data visualization libraries.
• Generate customer insights using RFM analysis, cohort analysis, and sequential pattern mining.
• Collaborate with cross-functional teams to deliver actionable insights and drive business growth.

Desired Candidate Profile:

Required skills to be successful:

• Bachelor's/MSc in Marketing Analytics, Computer Science, Statistics, or a related field.
• 5+ years of experience in customer analytics or data science.
• Proficiency in SAP CRM Emarsys, Python, SQL, Databricks, and machine learning libraries (scikit-learn, TensorFlow, PyTorch, ARIMA/SARIMA, Prophet).
• Experience with MLOps, Git, and data visualization tools (Matplotlib, Seaborn, Plotly).

About the team:
You will be part of a dynamic team that includes marketing, IT, and customer service departments. Our team is dedicated to leveraging data science to drive business growth and enhance customer experiences.

What equips you for the role:

• Proficiency in logistic regression, random forests, clustering algorithms (k-means, DBSCAN), survival analysis, gradient boosting machines, reinforcement learning, and decision trees.
• Advanced knowledge of RFM analysis, cohort analysis, and sequential pattern mining.
• Expertise in statistical techniques and data visualization for KPI development.
• Familiarity with NLP techniques for text analysis in customer feedback and communications.
• Hands-on experience with advanced statistics, machine learning, time series analysis, forecasting, regression, classification, clustering, dimensionality reduction, gradient boosting, neural networks, anomaly detection algorithms, hyper-parameter tuning, and natural language processing techniques.
• Strong problem-solving and critical thinking skills, with the ability to communicate technical concepts to non-technical stakeholders.
• Project management skills and the ability to work in cross-functional teams.
• Strong communication and collaboration skills.