Requirements: Job Description
The Senior Data Science Implementation Developer will be responsible for designing and developing Credit Risk Modelling and Decisioning modules of CreditX.
An Ideal candidate would have 5 to 8 years of Development experience mainly in the financial sector while leveraging different technologies and have had a demonstrated experience of being a self-learner who thrives on new challenges and stays up to date with the latest developments in the field. A background in Software Development within Financial Services, especially in Credit Modelling / Decisioning would be advantageous. She/He will be a key member of our Product Development team and also support in client deployment activities.
Additionally, the candidate should be able to assess problem and opportunity statements based on client feedback loops, competitive benchmarking and assessment of new market opportunities/revenue growth pools/use cases/new tech & data enhancements/emerging regulations. Work closely with CEO, CTO, commercial leaders and product delivery teams to champion and iteratively align product value proposition and experience.
Requirements: Key Responsibilities
· Develop and execute a product vision and strategy for near and long-term and build a dynamic product roadmap aligned to the company vision and growth ambition in existing and new markets.
· Lead the strategic planning and prioritisation of the product roadmap across markets – prioritise development initiatives to achieve business goals.
· Design and Develop core software with data intensive operations and statistical modelling techniques.
· Experience in Object Oriented programming and test-driven development approaches.
· Build products, prototypes, and MVPs to validate ideas by practically applying Data Science concepts.
· Rapid prototyping and experimentation to develop and validate Proof of Concepts (POCs) with leading global financial institutions.
· Work with large, diverse datasets using Big Data technologies and public cloud services.
· Translate end user needs to requirements using design thinking methodologies.
· Conduct data exploration, feature engineering, visualization and develop appropriate models.
· Familiarity with advanced statistical procedures and implement them into Production grade software modules.
· Cross-validate models to ensure their generalizability across various products.
· Develop and document non-technical reports that detail the successes and limitations of each project.
· Suggest ways in which insights obtained might be used to make informed decisions about business strategies.
Requirements: Skills
· A Bachelor’s degree in Computer Science, Data Science, statistics, or a similar field
· Must have 5 + years industry experience working in a software development role involving machine learning, deep learning, quantitative financial analysis and data engineering.
· Domain experience in Financial Services (banking, insurance, risk, fraud) is preferred.
· Have experience in producing and rapidly delivering minimum viable products, results focused with ability to prioritize the most impactful deliverables.
· Hands on experience preferable in implementing scalable Machine Learning solutions using Python / Scala / Java on Azure, AWS or Google cloud platform.
· Experience with Big Data frameworks like Hadoop, Spark, Kafka etc.
· Experience in building &deploying unsupervised, semi-supervised, and supervised models and be knowledgeable in various ML algorithms such as regression models, Tree-based algorithms, ensemble learning techniques, distance-based ML algorithms etc.
· Ability to track down complex data quality and data integration issues, evaluate different algorithmic approaches, and analyse data to solve problems.
· Experience in implementing parallel processing and in-memory frameworks.
