17 Apr
Sr. Data Scientist - Text Analytics
Vacancy expired!
- Partner with various departments (e.g., Product, Engineering, etc.) to frame problems, both mathematically and within the business context.
- Partner with Product and Engineering teams to bring models to production
- Debug Maintain, Tune, and Improve model behavior and performance with live data.
- Oversee and facilitate the training of a range of Machine Learning models.
- Evaluate the quality of the trained models, using existing and new measures
- Report on the current and historical state of our models' performance, along with issues and progress
- Incident resolution: Low accuracy troubleshooting, mis-categorization issue analysis
- Maintenance and improvement of the existing model development pipeline
- Produce ad-hoc analysis/investigations on the modelling pipeline
- Document parts of the modeling/testing process
- Support development, enhancement and maintenance of training datasets
- 5+ years of overall data science experience.
- At least 1 year on the job experience with Text Analytics and NLP (natural language processing) techniques and sparse data
- Advanced degree in economics, statistics, physics, math, or another quantitative field
- Strong grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus.
- Understanding of how and when to apply different Machine Learning algorithms
- Ability to write production-level code in Python, as well as proficiency with SQL
- Strong grasp of Pandas, NumPy, SciPy and Scikit-Learn Python packages, as well as other analytics packages in Python, or Spark
- Demonstrable analytical and problem-solving abilities, coupled with an enquiring mind and the ability to learn quickly
- Experience or familiarity designing and running both simulated and live experiments (A/B and multivariate tests) to drive KPI improvement
- Experience or familiarity building supervised and unsupervised models using statistical or machine learning approaches
- Ability to creatively problem-solve, and to thrive in a highly collaborative, multidisciplinary environment
- Measure and optimize products and business processes; to identify opportunities, assess risk potentials and explain trends; to drive audience and revenue growth
- Holistic and end to end approach to data, including querying, aggregation, deep analysis, visualization and models; communicate and present findings/actionable insights to audiences at varying levels of technical sophistication
- Assist in data requirements gathering and data validations to improve data platforms
- Flexible and adaptable to learn and understand new technologies
- Strong business acumen with ability to clearly articulate research goals and results to technical and business audiences
- Efficiently manage his/her own project queue and develop streamlined workflows
- Prior professional experience in the financial industry
- Ph.D. in economics, statistics, physics, math, or another quantitative field
- Ability to initiate and drive projects from ideation to implementation
- Prior professional experience building deep-learning models and familiarity with the popular frameworks (TensorFlow or PyTorch is a huge bonus)
- Experience with deep learning and other advanced modeling approaches to extract and automate insights from data
- Understanding of current trends in machine learning interpretability and transparency
Vacancy expired!