Data Scientist (hybrid)

About the Company

Our client is an innovative, data-driven organization committed to delivering exceptional customer experiences through advanced analytics, machine learning, and intelligent decision-making. By leveraging modern technologies and data science, the company develops personalized solutions that improve customer engagement, retention, and long-term business growth. The organization promotes a collaborative, inclusive, and flexible workplace where innovation, continuous learning, and professional development are encouraged.

About the Role

The company is seeking an experienced Data Scientist to join its Decision Sciences team in a hybrid work environment. This role focuses on developing predictive models, evaluating machine learning pipelines, and generating actionable insights that improve customer retention, engagement, and lifetime value.

The ideal candidate has strong expertise in machine learning, statistical modeling, Python, SQL, and customer analytics. You will collaborate closely with marketing, CRM, analytics, product, and business stakeholders to transform complex business challenges into scalable, data-driven solutions that support strategic decision-making.

Key Responsibilities

• Design, develop, and optimize machine learning models supporting customer retention, engagement, and lifetime value initiatives.
• Evaluate existing predictive models and data pipelines, identifying opportunities to improve model accuracy and business impact.
• Build churn prediction, customer segmentation, recommendation, and forecasting models.
• Develop marketing attribution, forecasting, and customer lifetime value (CLV) models to support business planning.
• Partner with CRM, marketing, product, and analytics teams to translate business objectives into data science solutions.
• Perform exploratory data analysis to identify customer behavior patterns, trends, and growth opportunities.
• Design, execute, and analyze A/B tests and controlled experiments to support evidence-based decision-making.
• Develop dashboards, reports, and data visualizations that communicate model performance and business insights.
• Build reusable data products and scalable analytical solutions.
• Monitor model performance and recommend continuous improvements using MLOps best practices.
• Write efficient SQL queries to extract, transform, and analyze large datasets.
• Communicate technical findings effectively to both technical and non-technical stakeholders.
• Maintain high standards of data quality, governance, and documentation.
• Stay current with advancements in machine learning, artificial intelligence, and predictive analytics.

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field; Master's degree preferred.
• 3+ years of professional experience in Data Science, Machine Learning, Marketing Analytics, or Customer Analytics.
• Advanced proficiency in Python for data analysis, statistical modeling, and machine learning.
• Strong SQL skills with experience querying large relational databases.
• Experience developing predictive models for customer retention, churn prediction, customer engagement, or recommendation systems.
• Strong understanding of statistical analysis, regression, hypothesis testing, causal inference, and experimental design.
• Experience designing and evaluating A/B testing and experimentation frameworks.
• Familiarity with MLOps concepts, model deployment, monitoring, and lifecycle management.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work collaboratively with cross-functional business and technical teams.

Preferred Qualifications

• Master's degree in Data Science, Artificial Intelligence, Statistics, or a related discipline.
• Experience working in e-commerce, marketing analytics, customer loyalty, subscription, or membership-based businesses.
• Experience using dbt or modern data transformation tools.
• Familiarity with Customer Lifetime Value (CLV) modeling techniques, including BG/NBD, Pareto/NBD, or machine learning-based approaches.
• Experience working with cloud-based analytics platforms and big data technologies.

Preferred Skills

• Data Science
• Machine Learning
• Predictive Analytics
• Python
• SQL
• Statistical Modeling
• Customer Analytics
• Customer Retention
• Churn Prediction
• Customer Lifetime Value (CLV)
• Forecasting
• Marketing Analytics
• CRM Analytics
• A/B Testing
• Experimental Design
• Causal Inference
• Regression Analysis
• Data Visualization
• Dashboard Development
• MLOps
• dbt
• Data Pipelines
• Feature Engineering
• Model Deployment
• Data Mining
• Business Intelligence
• Problem Solving
• Stakeholder Management
• Communication Skills
• Cross-Functional Collaboration

Benefits

• Competitive salary with performance-based bonus opportunities.
• Hybrid working model with flexible work arrangements.
• Comprehensive medical and healthcare benefits.
• Retirement savings and pension plan.
• Generous paid annual leave plus additional personal leave.
• Professional development budget and learning opportunities.
• Employee wellness initiatives and assistance programs.
• Modern office facilities with collaborative workspaces.
• Employee discount and rewards programs.
• Company-sponsored social events and team-building activities.
• Career advancement opportunities within a growing data-driven organization.

Equal Opportunity Employer

The hiring company is committed to fostering a diverse, equitable, and inclusive workplace where every employee is valued and respected. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by applicable laws. The organization believes that diversity of thought and experience drives innovation, strengthens collaboration, and contributes to long-term success.