Data Scientist (5-9 yrs)

As a Data Scientist, you will be working with the largest repository of corporate, board-level business information in the world. You will work with Product Managers, Business Analysts, Data Analysts, User Experience Designers, ML Engineers, and Senior Executives to gather requirements and apply data science methodologies to solve complex business problems.

You should have deep expertise in analyzing large, complex data sets from multiple domains, then translating this analysis to models which can run at scale in a SaaS business. You will be a part of an established global team focused on Analytics, Search and Artificial Intelligence with researchers in developers in Waltham, MA, Bucharest, Romania and Hyderabad, India all focused on the development of solutions for Investment Bankers, Private Equity and other industries.

Responsibilities & Opportunities of the Role :

- Work with the AI team in building world-class software, functioning as a thought leader in ensuring team development efforts resulting in the successful delivery of AI systems.

- Collaborate with cross functional agile teams of software engineers, data engineers, ML engineers, Product Managers, and others in building new product features

- Manage and execute entire data projects from start to finish including cross-functional project management, data gathering and manipulation, analysis and modelling, and communication of insights and recommendations.

- Demonstrate a high degree of originality and creativity when developing solutions to solve problems like entity recognition, document classification etc. utilizing methods such as statistical analysis, regression modelling, natural language understanding and optimization, and deep learning.

- Work independently to manage multiple projects at once while ensuring deadlines are met and data output is accurate and appropriate for the business. Must also be able to deal with ambiguity and make independent decisions about what data and approach is best for the task at hand.

- Think strategically about data as a core enterprise asset and assist in all phases of the advanced analytic development process

- Support advanced analytical and data mining efforts which could include but are not limited to clustering, segmentation, logistic and multivariate regression, decision/CART trees, neural networks, time-series analysis, sentiment analysis, topic modelling, random forests, and Bayesian analysis.

- The scope of work includes Forecasts, Prediction Models, Outlier Reporting, Risk Analysis, Document classification, Data Extraction, and Adhoc analysis.

- Implementation of Supervised and Unsupervised model development techniques

Experience :

- A minimum of 5 years of developing and running models in non-academic production systems. Please note that applications without this experience will not be considered. Some of this experience needs to with NLP and deep learning technologies.

- Masters or Ph.D. with experience in Machine Learning/Statistics/Data Science

- Experience with traditional as well as modern machine learning/statistical techniques, including Regression, Classification, Regularization, NLP, NLU, Ensemble Methods and Neural Networks

- Strong implementation experience with high-level languages, such as Python, R, Perl, Ruby, Scala or similar scripting languages.

- Familiarity with Linux/Unix/Shell environments.

- Strong hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of data.

- Strong written and oral communication skills.

- Intense intellectual curiosity - strong desire to always be learning

- Analytical, creative, and innovative approach to solving open-ended problems

- Highly collaborative, team-player attitude

- Experience with product development is a plus

- Experience with Financial Services is desired but not required. Much of our data relates to Investment Banking and M&A.

Technical Skills :

- Technical Skills: SAS &/or R &/or SPSS, Python, Hadoop, SQL, NoSQL, Unstructured Data, SQL, SparkSQL (or equivalent Big Data Language), Expert at MS Excel, XML, Data Visualization Tensorflow, Kubeflow, Anaconda, PyCharm, SciPy, Keras, Scikit, NLTK, SpaCY.

- Tool Experience (such as Tableau), XML, Web Services, Java, &/or Perl &/or Python &/or C/C++, RESTful Services and APIs, Testing and Debugging, Data Munging/Cleanup, Data Visualization and Communication.

- Experience with ML systems using frameworks such as Scikit-learn, Keras and Tensorflow.

- Technical/SDLC: General Agile experience, Strong SCRUM, Confluence, Jira, Version Control.

- Strong Presentation skills.

- Experience in business intelligence systems is a plus.

- Strong business acumen and financial services experience is a plus.