Aplazo - Data Scientist - IIT/IIIT/NIT/IISC

Data Scientist ( IITs / IIITs / NITs / IISC Tier 1 Only )

1.0 About Aplazo :

- Aplazo is a "buy now pay later" service based in Mexico that allows consumers to live their ideal lifestyle, making it easier to acquire the products they want. Through our platform, consumers can split their online and offline purchases into multiple installments without needing a credit card and avoiding the debt trap.

- Recently Aplazo has received Series A funding of $27 Million USD, and its team is growing in each vertical.

- We are setting out to make an impact on an epic scale. Aplazo enables merchants to connect with consumers in a creative, purposeful way, building more loyalty and trust between them.

- Aplazo's integrated, tech-enabled platform offers merchants the ability to increase average basket size, conversion, and customer engagement.

2.0 Summary of role :

- Define, monitor, and manage credit risk policies that take into consideration internal & external environments while supporting business growth in a fast-paced environment.

- Partner cross-functionally with our product and finance teams. Deliver machine learning-based risk solutions across credit risk and lead Aplazo's current risk and fraud decision models.

3.0 Reports to : Chief Data Scientist

4.0 Qualifications : Bachelor's or Master's degree in Computer Science, Information management, Statistics or related field, with 2 to 6 years of relevant work experience.

5.0 Location : India (Remote)

6.0 Nature of Employment : Permanent role

7.0 Compensation : 10 - 55 LPA + ESOPs + Perks

8.0 Responsibilities :

- Research, design, train and deploy machine learning solutions in domains such as NLP, Computer Vision, and more.

- Develop and embed the processes, tools, and policies needed to build robust credit strategies that are aligned to the business needs.

- Work closely with product teams to implement new products and features using ML/DL.

- Develop highly scalable classifiers and tools leveraging machine learning, deep learning, and rules-based models.

- Own the Data Science model end-to-end, from data collection to model building, to monitoring the model in production.

- Build Machine Learning and Deep Learning models in the customer lifecycle which include Personalization, Recommendation, Rewards, Referrals, Transaction Categorization, Customer Science-related models.

- Build production fraud and credit machine learning models; your models will decide to whom we lend in real-time.

- Conduct Data Analyses; your analyses will decide which policies we adopt, where we expand our business, and with whom we partner.

- Partner cross-functionally with our product and finance teams to drive strategy and optimize tactics as it relates to approval rates and conversion metrics through the funnel.

- Keep abreast of machine learning and industry developments, conduct R&D to incorporate best-in-class modeling methodologies, and disseminate learnings within the team.

9.0 Requirements :

- Bachelors or Master's degree in Computer Science, Information management, Statistics or related field.

- 1-4 years of relevant work experience in delivering projects using the agile methodology for Risk (preferably Credit Risk in Investment or Corporate Banking) and Finance projects.

- You should have an in-depth understanding of credit, risk, collections and are adept at building and deploying policies, models, and metrics.

- You enjoy partnering cross-functionally to drive core credit, risk, collection initiatives including risk appetite, and risk-based pricing.

- Python programming skill is a must.

- Experience with NoSQL databases such as MongoDB is a plus.

- Experience in statistical modeling, machine learning, data mining, unstructured data analytics, and natural language processing. Sound understanding of - Bayesian Modelling, Classification Models, Cluster Analysis, Neural Network, Nonparametric Methods, Multivariate Statistics, etc.

- Experience in Machine learning ensemble models such as Xgboost, Lightgbm, etc.

- Strong in data analysis and data wrangling. Experience with common libraries and frameworks in data science.

- Familiarity with database queries and data analysis processes (SQL, Python)

- Outstanding leadership, influencing, communication, interpersonal, and teamwork skills.

- Detail-oriented, with the ability to work both independently and collaboratively.

- Any prior research publication is a plus point.

10.0 Preferences :

- People who demonstrate high ownership and have a founder's mindset

- People with an endless curiosity and hunger to learn

- Operators obsessed with customer experience

- Excellent communication and interpersonal skills

- Employment Type

- Full-time