Concentrix
Website:
concentrix.com
Job details:
About the job
We’re Concentrix. A new breed of tech company — Human-centered. Tech-powered. Intelligence-fueled.
We create game-changing solutions across the enterprise, that help brands grow across the world and into the future. We are trusted by clients across all major sectors, from up-and-coming success stories to iconic Fortune Global 500 brands in over 70 countries spanning 6 continents.
Our game-changers:
* Challenge Conventions
* Deliver outcomes unimagined
* Create experiences that go beyond WOW
If this is you, we would love to discuss career opportunities with you.
In our Information Technology and Global Security team, you will deliver the latest technology infrastructure, transformative software solutions and industry-leading global security for our staff and clients. You will work with the best in the world to design, implement and strategize IT, security, application development, innovation, and solutions in today’s hyperconnected world. You will be part of the technology team that is core to our vision of develop, build and run the future of CX.
Concentrix provides eligible employees with an opportunity to enroll in many benefit programs, generally including private medical plans, great compensation package, retirement savings plans, paid learning days, and flexible workplaces. Specific benefits plans will vary by country/region.
- We’re a remote-first company looking for the absolute best talent in the world. Experience the power of a game-changing career.
Data Scientist – Collections Analytics (ML Propensity Modeling)
Location: Mumbai (Hybrid/Remote)
Experience: 7+ Years
Employment Type: Full-Time
About the Role
We are seeking an experienced Data Scientist to design, develop, and deploy Machine Learning-based Propensity Models to support Collections Analytics initiatives for a leading automotive client. The role will involve working closely with business stakeholders, analytics teams, and client counterparts to identify opportunities for improving collections effectiveness, customer engagement, and recovery strategies through advanced predictive analytics.
The ideal candidate will possess strong machine learning expertise, hands-on model development experience, and excellent communication skills to collaborate effectively with client stakeholders and translate business requirements into analytical solutions.
Key Responsibilities
Machine Learning & Analytics
- Design, develop, validate, and deploy propensity models for collections and customer behavior prediction.
- Build predictive models to identify customers with varying probabilities of payment, delinquency, default, or recovery.
- Apply advanced statistical and machine learning techniques to solve business problems.
- Perform feature engineering, model selection, hyperparameter tuning, and performance evaluation.
- Monitor model performance and recommend enhancements to improve prediction accuracy.
- Develop segmentation strategies and analytical frameworks to optimize collections outcomes.
Data Management & Insights
- Analyze large structured and unstructured datasets to uncover actionable insights.
- Conduct exploratory data analysis (EDA) and data quality assessments.
- Collaborate with data engineering teams to prepare and maintain analytical datasets.
- Create dashboards, reports, and presentations to communicate findings and recommendations.
Stakeholder & Client Engagement
- Work directly with client and operations stakeholders to understand business requirements and translate them into analytical solutions.
- Present analytical findings, model outcomes, and business recommendations to technical and non-technical audiences.
- Partner with collections, operations, and technology teams to drive implementation of analytical solutions.
- Provide consulting support on collections strategy optimization using data-driven approaches.
Required Skills & Qualifications
Technical Skills
- 7+ years of experience in Data Science, Predictive Analytics, or Machine Learning.
- Strong expertise in building and deploying predictive/propensity models.
- Hands-on experience with:
- Python (Pandas, NumPy, Scikit-learn, XGBoost, LightGBM)
- SQL
- Machine Learning algorithms
- Statistical Analysis and Predictive Modeling
- Strong experience in defining the strategy to measure business benefits post solution deployment.
- Experience working with large-scale datasets and data mining techniques.
- Strong understanding of model evaluation metrics and validation methodologies.
- Experience with cloud platforms such as Azure, AWS, or GCP is preferred.
- Familiarity with MLOps and model deployment frameworks is an advantage.
Domain Experience
- Experience in Collections Analytics, Credit Risk, Financial Services, Banking, Automotive Finance, or Customer Analytics is highly preferred.
- Understanding of customer lifecycle analytics, debt collection strategies, and propensity modeling use cases.
Communication & Consulting Skills
- Excellent verbal and written communication skills.
- Strong client-facing experience and stakeholder management capabilities.
- Ability to simplify complex analytical concepts for business audiences.
- Experience working in global and cross-functional teams.
Preferred Qualifications
- Master's degree or Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field.
- Experience with lending analytics is a plus.
Success Measures
- Successful development and deployment of collection propensity models.
- Improvement in collections effectiveness and recovery rates.
- Delivery of actionable insights that drive business value.
- Strong stakeholder satisfaction and effective collaboration with Client teams.
Keywords
Collections Analytics, Propensity Modeling, Machine Learning, Predictive Analytics, Customer Analytics, Credit Risk, Python, SQL, Data Science, Collections Strategy, XGBoost, Classification Models, Predictive Modeling, ML OPs
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