Mahindra Finance - Lead - Data Sciences

Organisation:

Mahindra Group is building the next generation digital fintech organization to serve Indian customers with innovation and disruption using technology as a key driver.

The entity Digital Finco is being run like a separate independent startup/company inside of Mahindra Finance. Digital Finco will focus on the full suite of financial products for individuals and enterprises in both rural and urban markets.

Digital Finco has started operations under the Mahindra Finance umbrella, with a very distinct organizational culture of high performance, rewards, agility, and a digital-first mindset to build a profitable and real-world business resonating with the Mahindra Groups philosophy of accepting no limits, alternative thinking and driving positive change.

Role:

The opening is in Mumbai for Lead - Data Science who will lead the areas of

- Identifying and phrasing problem statements, identifying data needed to solve the problem, designing mechanisms to solve the data problem, and delivering the working solution.

- Candidate will be the key person interacting with the business teams and vendors for the project and will also direct the analysts working on the projects.

- Candidate will be reporting to the Head of Data Science team who is a renowned leader in the field of data sciences.

- Mahindra Finance Digifinco team is recruiting for a Lead Data Scientist to lead a technical team and help us gain useful insight out of raw data.

- Lead Data Scientist responsibilities include managing the data science team, planning projects, and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis.

- Candidate should be able to align our data with our business goals. Your ultimate responsibility will be to help improve our products and business decisions by making the most out of our data.

- Strong analytical and reasoning skills that result in clear technical execution.

- Hands-on and efficient in writing complex SQL queries for all test cases (Unit/System/functional/Data reconciliation/etc.)

- Must have Design and development experience using Microsoft SQL Server Integration Services (SSIS) and performance tuning of SSIS.

- Strong experience in data modeling, data migration, and a good understanding of BI & DWH development methodologies.

- Strong Experience with Data governance (Data Quality, Metadata Management, Security, etc.)

- Engineer and orchestrate data flows and pipelines in a cloud environment using a progressive tech stack (SQL, ETL (SSIS), AZURE DB, AZURE DWH, Data Lake, Hive)

- Skilled at translating requirements into clean, efficient, quality code which is scalable and easy to maintain.

Responsibilities:

- Coordinate with multiple stakeholders like Operations, Data Science and other IT Data teams to effectively manage the data environment

- Excellent organizational and time management skills with the ability to manage multiple priorities to accomplish the objectives and goals anticipating and adjusting for problems and interruptions/roadblocks

- Solid understanding and experience practicing Agile software development methodologies

- Dealing with the Operational teams from multiple business teams in the companies. This may include interactions with Product, Operations, Sales, Marketing and IT heads from business teams. It includes the following key aspects:

Communicate and understand clearly what the business-data challenges are

Culturally sensitizing business teams to be open to sharing and using data to solve problems and letting machines make certain decisions using AI.

Knowing the art of identifying what data needs to be extracted/ used to solve a particular challenge.

Designing a consumption layer for the business teams to consume the final delivered solution

Explain to business teams what the solution is doing behind the curtains in a very simplified manner.

- Dealing with Data Science Vendors

Summarize the business data challenges to them and provide clear deliverables

Timely interfacing with the vendors in resolving their requests and queries.

Testing and verifying their deliverables and refining them.

Maintain a healthy relationship with key vendors

- Managing internal project team and Science behind projects

Managing analysts on the project - work distribution and timeline planning for the projects, training and guiding the analysts

Designing the frameworks in data sciences (R, Python, Azure ML, Amazon ML, Google ML, Spark, etc.) to be used for relevant projects

Choice of Data and Machine learning algorithms to solve a particular problem

- Creating Data Strategy roadmaps for businesses in the long term. Creating a "post project delivery way forward" to ensure the sustainability of data science solutions delivered.

- Being aware of the world-class and most recent advances in data science areas and having ready references to the best methods in the data science fraternity

- Displaying thought leadership on social media on all things data science

- Proactively identifying applications and ideas for using data science across Mahindra Finance

- Helping other teams at Mahindra Finance. with consultations on data expertise

Qualifications:

- Masters /Ph.D. Degree in Engineering (CS, EE, Mathematics), showing extreme rigor in mathematical and algorithmic thinking, preference for candidates with publications/patents/ premier institutions.

- 8 - 12 years of experience working as a data scientist in the finance industry

- Most important: Work experience in leading and delivering Data Science projects to business teams. Work experience may include problems in Financial Analytics, Lending Algorithms, Marketing Analytics, Semantic Analysis, Social Media Analytics, Operational Problems like Inventory, Supply Chain Optimization, Revenue/Pricing/Product Analytics, etc.

Knowledge:

Knowledge of key Data Science tools like Python-based machine learning and Cloud-based ML-like Azure ML

- Understanding of what algorithms need to be used to solve different classes of data problems

- Consulting skills like understanding business challenges, framing problem statements, delivering concise reports/ decks for CXO level consumption.

Skills:

A high degree of Emotional Intelligence in managing relationships with business leaders. Most of the data challenges will involve dealing with department heads from marketing, IT, finance, etc., and would need convincing the business teams of what data needs to be shared and how it will be used. There is a need to have the skill of selling the use of Machine Learning in conjunction with humans. A person needs to have a personality, composure, and body language equivalent to that of a consultant.

Competencies:

- Result Orientation with Execution Excellence

- Customer Focus

- Weaving passion and energy at work