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Tookitaki provides softwares to enable sustainable regulatory compliance programs

Lead Datascience, Singapore

$84k – $108k • 0.1% – 0.15%
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Location: Singapore (Singaporean/PR/EP)

About Tookitaki

We are a machine learning powered advanced forecasting platform, focussed on compliance and operational risk management space. Our primary clients are banks and financial institutions. We are bringing a paradigm shift in the approach of risk forecasting, by helping BFS sector move from static rules engine to dynamically adaptive platform. The key highlights are - ability to choose from multiple non-linear models, improve model performance over time through self-learning technique and deploy models in production faster via pre-packaged distributed environment.

Data science @ Tookitaki

The data science team is responsible for solving business problems on complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible. We also encourage to participate in competitions like Kaggle.

Our ideal candidate

We are looking for a lead data scientist who has deep interest in theoretical and applied machine learning and loves working in a fast-paced environment. He should be top rank holders in Kaggle.

He should have 3-5 years work experience in predictive analytics/forecasting space and have solved real-world problems. Candidates with experience in operational risk modeling, credit risk modeling in finance vertical would be given preference.

The role would be a client facing, hence good communication skills are a must. He should have an unique ability to communicate complex models and analysis in a clear and precise manner. He would be responsible for -

Comprehend business problem properly - what to predict, how to build DV, what value addition he is bringing to the client etc
Understand and analyze large, complex, multi-dimensional datasets and build feature matrix relevant for business
Understand the math behind algorithms and is able to choose one over another
Understand approaches like stacking, ensemble and apply them rightly to increase accuracy
Present solution to the client and ensuring PoV (Proof of value) success
Mentor and collaborate with junior data scientists to ensure delivery is done on time and with quality.
Research on ML algorithms related to operational and credit risk models and write code in python.
Coordinate with engineering team to incorporate models in the platform. We would also like to see him incorporating models in the platform himself - for this he needs to pick up scala language.

Desired technical requirements

You have familiarity with Python/R.
You are familiar with SQL and other data manipulation tools and packages.
You have solved various Kaggle problems and are one among the top performers.

Educational/Professional Requirement

MS or PhD in Maths, Applied Math, Statistics, Neural Network, Machine Learning from Tier-I college
Work Experience: 3-5 yrs
Preferable if Singaporean or Singaporean PR. EP candidates can apply.

Job Perks

Pay package decided by merit and not by last drawn CTC
Development machine of your choice ( Mac, Windows or Linux).
No fixed working hours and WFH in place.
Unlimited access to renowned AI, ML books
Health Insurance benefits covering outpatient and hospitalization
Telephone bill claims up to SGD 40 per month
Support for publishing work @ Tookitaki in international journals
Everything good at a start-up

Recent achievements

Winner of Fintech MAS-SME category
Among Top 3 forecasting companies chosen by McKinsey for their Innovation Forum

Tookitaki at a glance

Tookitaki provides softwares to enable sustainable regulatory compliance programs

Tookitaki focuses on Machine Learning, Banking, Predictive Analytics, and Fin Tech. Their company has offices in Singapore and Bengaluru. They have a small team that's between 11-50 employees. To date, Tookitaki has raised $31.2M of funding; their latest round was closed on February 2017.

You can view their website at http://www.tookitaki.com or find them on Twitter, Facebook, and LinkedIn.

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