World’s leading analytics firm looking for a top-notch Engineer to build algorithmic trading systems for an Artificial Intelligence led investment business. Unique opportunity to create an end-to-end technology platform – from data storage, testing and simulation of trading strategies, to live trading in the stock markets. Become a member of the core team pioneering this business on a well-supported platform.
Some of the attractive pluses of the job are:
A real opportunity to expand your skill-sets and a chance to learn and use the latest advances and approaches in machine learning and data mining on real-world datasets
Working at a fast-paced work environment where you are expected to be self-motivated and are measured by your performance.
- Ability to understand a problem statement and implement analytical solutions & techniques independently or with minimal supervision
- Work and collaborate with other teams to deliver and create value for clients
- Fast learner: ability to learn and pick up a new language/tool/ platform quickly
- Conceptualize, design and deliver high-quality solutions and insightful analysis
- Conduct research and prototyping innovations; data and requirements gathering; solution scoping and architecture; consulting clients and client facing teams on advanced statistical and machine learning problems.
- Ability to deliver AIML based solutions around a host of domains and problems, with some of them being: Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization
- 3+ years relevant experience in Regression, Machine Learning, Deep learning etc
- Intermediate to expert level proficiency in at least one of R and Python
- Ability to discover effective solutions to complex problems. Strong skills in data-structures and algorithms.
- Experience of working on a project end-to-end: problem scoping, data gathering, EDA, modeling, insights, and visualizations
- Problem-solving: Ability to break the problem into small problems and think of relevant techniques which can be explored & used to cater to those
- Intermediate to advanced knowledge of machine learning, probability theory, statistics, and algorithms. You will be required to discuss and use various algorithms and approaches on a daily basis.
- We use regression, Bayesian methods, tree-based learners, SVM, RF, XGBOOST, time series modeling, dimensionality reduction, SEM, GLM, GLMM, clustering etc on a regular basis. If you know few of them you are good to go.
Good to Have:
Experience in one of the upcoming technologies like deep learning, NLP, image processing, recommender systems
B.Tech / M.Tech in Computer Science / Mathematics / Signal Processing or related fields from one of the premier Institutes (IITs/NITs/BITS)