Principal Data Scientist

Job Description:

• Build pipelines for data acquisition by writing code for querying huge amounts of unstructured textual data from a variety of data sources like Financial SEC filings of publicly traded companies, private & public company press releases, co. transcripts, bond offering memorandum docs, etc.  using Elasticsearch & RMySQL frameworks in R & database software like HeidiSQL to query databases like MySQL & MongoDB.
• Utilize frameworks like XML, rjson, pdftools in R to parse & process data from different sources & formats incl. .pdf, XML, json, csv etc. & store it in a structured & organized format for data processing, analysis, & modeling.
• Devise & implement processes to perform data preprocessing & assessment of data quality text processing & statistical techniques incl. imputation to handle missing data, data type conversions to maintain consistency in data integration, dimensionality reduction, normalization, feature aggregation, encoding, etc.
• Leverage frameworks in R incl. OpenNLP, Quanteda, tm, text2vec to provide comprehensive functionality for text analysis & natural language processing. Utilize frameworks daily for a variety of tasks incl. corpus creation & management, tokenization, formulation of doc. feature matrices, parts-of-speech tagging, entity extraction, etc. to generate analysis for data exploration, engineer features, formulate details of the model, & overall bld. robust frameworks for projects.
• Execute defined frameworks for project that req. data-driven solutions by building, execute, & test various data science models or enhance existing models using text mining & machine learning algorithms. Track & monitor model’s performance by testing & debugging when req. Incorporate feedback, business requests from stakeholders to continually improve & enhance workflow & performance. 
• Conceptualize & build supervised &/or unsupervised models from structured &/or unstructured text data.
• Generate static & interactive data visualizations using frameworks & tools incl. ggplot, Shiny, d3.js to share & present complex ideas, results, project takeaways w/ tech. & non-tech. stakeholders.
• Review, evaluate, & communicate recommendations on modeling techniques & results to team, leadership, & stakeholders. Develop case studies using model output & suggest ways insights might be used.
• Deploy models in real-time by writing production-level code for scalable models & integrating it w/in the company’s data infrastructure.
• Collaborate & participate w/ different business units across the company to identify areas where data science can be used to automate manual processes.
• Mentor & lead new & junior members of the team.
• Formulate & implement ideas at intersection of distressed debt investing & data science, develop credit-risk models & transform into data products.

Education and Experience: Requires a Master’s degree in Data Science and 4 years of experience in job offered or 4 years of experience in the Related Occupation.  Experience can be pre or post degree.

Related Occupation: 

2 years of experience as a Data Scientist or any other job title performing the following job duties:

• Build pipelines for data acquisition by writing code for querying huge amounts of unstructured textual data from a variety of data sources like Financial SEC filings of publicly traded companies, private & public company press releases, co. transcripts, bond offering memorandum docs, etc.  using Elasticsearch & RMySQL frameworks in R & database software like HeidiSQL to query databases like MySQL & MongoDB.
• Utilize frameworks like XML, rjson, pdftools in R to parse & process data from different sources & formats incl. .pdf, XML, json, csv etc. & store it in a structured & organized format for data processing, analysis, & modeling.
• Devise & implement processes to perform data preprocessing & assessment of data quality text processing & statistical techniques incl. imputation to handle missing data, data type conversions to maintain consistency in data integration, dimensionality reduction, normalization, feature aggregation, encoding, etc.
• Leverage frameworks in R incl. OpenNLP, Quanteda, tm, text2vec to provide comprehensive functionality for text analysis & natural language processing. Utilize frameworks daily for a variety of tasks incl. corpus creation & management, tokenization, formulation of doc. feature matrices, parts-of-speech tagging, entity extraction, etc. to generate analysis for data exploration, engineer features, formulate details of the model, & overall build robust frameworks for projects.
• Execute defined frameworks for project that req. data-driven solutions by building, execute, & test various data science models or enhance existing models using text mining & machine learning algorithms. Track & monitor model’s performance by testing & debugging when req. Incorporate feedback, bus. requests from stakeholders to continually improve & enhance workflow & performance. 

and 2 years of experience as an Analyst or any other job title performing the following job duties:

• Evaluating alternative datasets like – Consumer Transactional, Email Receipt, URL Clickstream, OTA Pricing/Booking, Import/Export Shipments, Geolocation data & performing analysis to study & track market shifts, industry trends, & user dynamics. Generating actionable insights used in developing the investment thesis for the Long Short Equity Strategy.
• Utilizing PostgreSQL & Microsoft SQL Server for database querying, data retrieval, pre-processing & tagging.
• Performing predictive analytics on big data which incl - data munging, data validation, normalization, regression analysis, back testing, data visualization using tools like Python, SQL, Excel, & Tableau. Identifying abnormalities & opportunities & recommending trades to the trading desk.
• Building predictive models to forecast co. KPIs like “Revenue”, “Orders/Transaction Volume”, “Attendance”, etc. for publicly traded co. in the US Consumer sector. Developing techniques to analyze user retention & churn & built models that predict subscribers for co. in the OTT streaming & Cable sector.
• Developing novel data-driven processes using natural language processing techniques onto alternative data to drive qualitative analyses & building KPI prediction models - like development. Leveraging natural language processing & machine learning algorithms.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $170,373 to $210,000. 

The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors. This position is eligible for additional commission-based compensation.