Lead Engineer - Data Quality

The role is with a Fintech Credit Card company based in Pune within the Decision Science team. (OneCard )

About

Credit cards haven't changed much for over half a century so our team of seasoned bankers, technologists, and designers set out to redefine the credit card for you - the consumer. The result is OneCard - a credit card reimagined for the mobile generation. OneCard is India's best metal credit card built with full-stack tech. It is backed by the principles of simplicity, transparency, and giving back control to the user.

The Engineering Challenge

“Re-imaging credit and payments from First Principles”

Payments is an interesting engineering challenge in itself with requirements of low latency, transactional guarantees, security, and high scalability. When we add credit and engagement into the mix, the challenge becomes even more interesting with underwriting and recommendation algorithms working on large data sets. We have eliminated the current call center, sales agent, and SMS-based processes with a mobile app that puts the customers in complete control. To stay agile, the entire stack is built on the cloud with modern technologies.

Purpose of Role :

- Develop and implement the collection analytics and strategy function for the credit cards. Use analysis and customer insights to develop optimum strategy.

CANDIDATE PROFILE :

- Successful candidates will have in-depth knowledge of statistical modelling/data analysis tools (Python, R etc.), techniques. They will be an adept communicator with good interpersonal skills to work with senior stake holders in India to grow revenue primarily through identifying / delivering / creating new, profitable analytics solutions.

We are looking for someone who:

- Proven track record in collection and risk analytics preferably in Indian BFSI industry. This is a must.

- Identify & deliver appropriate analytics solutions

- Experienced in Analytics team management

Essential Duties and Responsibilities :

- Responsible for delivering high quality analytical and value added services

- Responsible for automating insights and proactive actions on them to mitigate collection Risk.

- Work closely with the internal team members to deliver the solution

- Engage Business/Technical Consultants and delivery teams appropriately so that there is a shared understanding and agreement as to deliver proposed solution

- Use analysis and customer insights to develop value propositions for customers

- Maintain and enhance the suite of suitable analytics products.

- Actively seek to share knowledge within the team

- Share findings with peers from other teams and management where required

- Actively contribute to setting best practice processes.

Knowledge, Experience and Qualifications :

Knowledge :

- Good understanding of collection analytics preferably in Retail lending industry.

- Knowledge of statistical modelling/data analysis tools (Python, R etc.), techniques and market trends

- Knowledge of different modelling frameworks like Linear Regression, Logistic Regression, Multiple Regression, LOGIT, PROBIT, time- series modelling, CHAID, CART etc.

- Knowledge of Machine learning & AI algorithms such as Gradient Boost, KNN, etc.

- Understanding of decisioning and portfolio management in banking and financial services would be added advantage

- Understanding of credit bureau would be an added advantage

Experience :

- 4 to 8 years of work experience in core analytics function of a large bank / consulting firm.

- Experience on working on Collection analytics is must

- Experience on handling large data volumes using data analysis tools and generating good data insights

- Demonstrated ability to communicate ideas and analysis results effectively both verbally and in writing to technical and non-technical audiences

- Excellent communication, presentation and writing skills Strong interpersonal skills

- Motivated to meet and exceed stretch targets

- Ability to make the right judgments in the face of complexity and uncertainty

- Excellent relationship and networking skills across our different business and geographies

Qualifications :

- Masters degree in Statistics, Mathematics, Economics, Business Management or Engineering from a reputed college

• Work in collaboration with the application team and integration team to design, create, and maintain optimal data pipeline architecture and data structures for Data Lake/Data Warehouse.
• Work with stakeholders including the Sales, Product, and Customer Support teams to assist with data-related technical issues and support their data analytics needs.
• Assemble large, complex data sets from third-party vendors to meet business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Elasticsearch, MongoDB, and AWS technology.
• Streamline existing and introduce enhanced reporting and analysis solutions that leverage complex data sources derived from multiple internal systems.

• 5+ years of experience in a Data Engineer role.
• Proficiency in Linux.
• Must have SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with databases including Mysql, Mongo, Cassandra, and Athena.
• Must have experience with Python/Scala.
• Must have experience with Big Data technologies like Apache Spark.
• Must have experience with Apache Airflow.
• Experience with data pipeline and ETL tools like AWS Glue.
• Experience working with AWS cloud services: EC2, S3, RDS, Redshift.

Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.

What will you do?

• You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
• You will be constantly assessing and improving the model using techniques like Transfer learning
• You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
• You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
• Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
• Building predictive models and machine-learning algorithms to apply to data sets.
• Coordinate with different functional teams to implement models and monitor outcomes.
•  
• Presenting information using data visualization techniques and proposing solutions and strategies to business challenges

We would love to hear from you if :

• You have 2+ years of experience as a software engineer at a SaaS or technology company
• Demonstrable hands-on programming experience with Python/R Data Science Stack
• Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
• Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
• Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
• Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
• Preferable Experience Experienced in web crawling and data scraping
• Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
• Experience with text mining, pattern matching and fuzzy matching

• Brand new Macbook
• Stock Options
• Health Insurance
• Unlimited Sick Leaves
• Passion Fund (Invest in yourself or your passion project)
• Wind Down

• Drive and participate in requirements gathering workshops, estimation discussions, design meetings and status review meetings
• Participate and contribute in Solution Design and Solution Architecture for implementing Big Data Projects on-premise and on cloud
• Technical Hands on experience in design, coding, development and managing Large Hadoop implementation
• Proficient in SQL, Hive, PIG, Spark SQL, Shell Scripting, Kafka, Flume, Scoop with large Big Data and Data Warehousing projects with either Java, Python or Scala based Hadoop programming background
• Proficient with various development methodologies like waterfall, agile/scrum and iterative
• Good Interpersonal skills and excellent communication skills for US and UK based clients

We are a nascent quantitative hedge fund led by an MIT PhD and Math Olympiad medallist, offering opportunities to grow with us as we build out the team. Our fund has  world class investors and big data experts as part of the GP,  top-notch ML experts as advisers to the fund, plus has equity funding to grow the team, license data and scale the data processing.

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

• Atleast 3 years of relevant ML experience
• Graduation date : 2018 and earlier
•   3-5 years of experience in high level Python programming.
• Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
•   Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques. 
•   Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
• Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
•   Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling. 
•   Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
•   A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
• A valid Github profile with some activity in it

Bonus to have:

•   Experience in storing and retrieving data from large and complex time series databases
•   Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
•   Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation. 
•   Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.) 
•   Knowledge of REST APIs and data extracting and cleaning techniques 
•   Good to have experience in Pyspark or any other big data programming/parallel computing
•   Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
•   Any progress towards CFA or FRM is a bonus
• Average tenure of atleast 1.5 years in a company