Data & Analytics Manager

Background

Through technology and advanced analytics, Nikel offers a range of products to our customers in Indonesia, including Customer Acquisition, Credit Card Onboarding and Management, Lending Onboarding and Management, Fraud Detection System, Credit Decision Engine and Risk & Analytics Consulting. Our mission is to drive business growth by providing secure, efficient, and inclusive financial solutions. Website: https://nikel.com/

Job Summary

We are seeking an experienced Data & Analytics Manager to lead and manage the data and analytics strategy, focusing on data management, predictive analytics, machine learning, and intelligent automation. The ideal candidate will drive the implementation of data and analytics products and services, ensuring alignment with customer needs, particularly in the areas of lending, credit, and payment risk management. You will lead cross-functional teams and collaborate with stakeholders to deliver innovative data solutions that enable informed decision-making and business growth.
 

Key Responsibilities

• Develop and implement strategies for data management, governance, and quality assurance across the organization.
• Oversee the design, architecture, and implementation of data solutions to ensure accuracy, security, and accessibility.
• Utilize advanced analytics and machine learning models to derive insights and predict trends, customer behaviors, and business opportunities.
• Lead the end-to-end development, deployment, monitoring, and maintenance of predictive models to improve risk management, customer segmentation, and operational efficiency. This includes establishing model performance metrics, model retraining strategies, and model version control.
• Spearhead the integration of intelligent automation tools into business processes to streamline operations and reduce manual effort.
• Lead customer-facing projects to implement data and analytics solutions, ensuring timely delivery and successful adoption.
• Collaborate with clients to tailor solutions to meet specific business needs in the lending, credit, and payment risk domains.
• Establish and maintain a robust MLOps (Machine Learning Operations) pipeline for continuous integration, continuous delivery, and continuous training of machine learning models.

Qualifications

• Degree in a quantitative discipline: Mathematics, Statistics, Data Science, Computer Science, Statistics, Engineering, or a related field. 
• 7+ years of experience in data analytics, data management, or related roles.
• Experience in predictive analytics, machine learning, and implementing intelligent automation solutions.
• Strong understanding of lending, credit, and payment risk products and processes.
• Proficient in tools such as Python, R, SQL, and data visualization tools (Tableau, Power BI, etc.).
• Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud for data processing and model deployment.
• Excellent communication and stakeholder management skills, with experience working directly with clients or customers.
• Strong project management skills with a demonstrated ability to deliver complex solutions on time and within budget.
• Familiarity with risk management frameworks and regulatory requirements is a plus.
• Experience in operationalizing machine learning models, including model deployment, monitoring, and maintenance in a production environment is a plus.
• Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, AWS SageMaker) is highly desirable.
• Certification in data science, or project management is a plus.

Benefits

• Challenging role in a startup environment with strong growth ambitions.
• Opportunities for professional growth and development.
• A dynamic and innovative work environment.
• Competitive compensation and benefits

At Nikel, we are committed to diversity and equitable access to employment opportunities based on ability. Interested candidates can send their applications to [email protected]. We thank all applicants for their interest but will only contact candidates selected to advance in the hiring process.