About 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.
- 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
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
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.
- 1st : INR 2,00,000
- 2nd : INR 1,00,000
- 3rd : INR 50,000
Top scorers also get a chance to interview with LTFS for roles in Advanced Analytics team based in Mumbai.
- 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 with LTFS 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 and LTFS 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
- 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.