LTFS Data Science FinHack ( ML Hackathon)

L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’.

Amazing opportunity for all creative nerds to apply their data science & machine learning skillset to best solve a real business problem.

In this FinHack, you will develop a model for our most common but real challenge ‘Loan Default Prediction’ & also, get a feel of our business!

If your solution adds good value to our organization, take it from us, Sky is the limit for you!

About L&T Financial Services (LTFS):

Headquartered in Mumbai, LTFS is one of India’s most respected & leading NBFCs providing finance for two wheeler, farm equipment, housing, infra & microfinance. With a strong parentage & stable leadership, it also has a flourishing Mutual Fund & Wealth Advisory business under its broad umbrella.

Our Advanced Analytics team,

• Solves only ‘Real’ Business Problems through Data
• Enables business decisioning across all verticals
• Harnesses external data (incl. mobile, social media, bureau, socio economic etc)
• Utilises non-conventional and innovative data science approaches

LTFS was featured in "Forbes Super 50 Companies“(August 2018)

To know more about LTFS, please visit:www.ltfs.com.

Follow us:

• FB: https://www.facebook.com/LnTFS/
• Twitter: https://twitter.com/LnTFSOnline/
• Youtube: https://www.youtube.com/user/ltfinance
• Linkedin: https://in.linkedin.com/company/l&t-finance

About the Job Role:

Positions: Data Scientist

Location: Mumbai

Minimum Qualification: BTech/MTech/MS in Stats/Maths/Economics/Analytics and an Analytical Mind!!

Relevant Work Experience: 2+ Years

Mandatory Skillset: Creative thinking, Analytical mindset, Conceptualising & Problem Solving

Summary of Responsibilities

• Collaborate with fellow data scientists, business teams & internal stakeholders
• Conceptualise business problems, design & deliver superior analytical solutions
• Independently handle project work streams with minimum supervision
• Think, think, think……. & lastly, deliver & execute

Desired Skills

• Proven background in at least one: Regression Models – Logistic/Linear, Stochastic Models, Bayesian Modeling, Classification Models, Cluster Analysis, Neural Network, Non-parametric Methods, Multivariate Statistics;

• Proficiency in at least one statistical and other tools/languages – R/Python/SAS;
• Familiarity with relational databases and intermediate level knowledge of SQL;

Experience working with large data sets and tools like MapReduce, Hadoop, Hive, etc would be an advantage

Who all can Participate?

• Open for all data enthusiasts: Statisticians, Data scientists, Analysts, and Students.

• LTFS employees are not allowed to participate in the competition.

Prizes:

• 1st : INR 2,00,000
• 2nd : INR 1,00,000
• 3rd : INR 50,000

Top scorers also get a chance tointerview with LTFSfor roles in Advanced Analytics team based inMumbai.

Rules:

• Entries submitted after the contest is closed, will not be considered
• Individual participation is allowed in the hackathon, and participant can either be a part of a team or can participate individually.
• Multiple IDs of user leads to disqualification from the contest
• Use of external data is not allowed
• Participants who are interested in a job opportunity withLTFS must update their profile details and upload their latest CV
• The decision on the winners and runners-up made by Analytics Vidhya &LTFS will be final and binding
• Throughout the hackathon, you are expected to respect fellow hackers and act with high integrity
• Analytics Vidhya andLTFS hold the right to disqualify any participant at any stage of competition if the participant(s) are deemed to be acting fraudulently.
• Cash prizes will be subject to TDS (Tax Deduction at Source) as per Indian Iaws.
• In case any winners in top 3 are outside of India, they will need to provide required documents (tax residency certificate, passport, bank account details, etc.) as required by Indian laws

Team Formation

• Click here to view process flow for Team Creation
• Maximum of 2 people can form a team.
• One person can be a part of one team only.
• In case a team wins, prize would be distributed equally among team members
• Team once created can't be dissolved.
• Teams can't be merged.