Principal Data Scientist

New York
US$130000 - US$150000 per year + Bonus


Based in Dallas- Fort Worth, a specialized asset management firm is growing.. It utilizes applied intelligence to unlock the full potential of real estate, a massive market that defines the American Dream. The team is creating innovative and actionable algorithms to reveal research-based secrets pulled from massive data sources, in order to get ahead of today's market and take the next biggest step in growing out AUM for not only their firm but carving a path for all AM firms moving forward. The core business is focusing on building automated decisioning tools using artificial intelligence and machine learning to drive our complex pricing models and provide a base for long-term and short-term loan performance prediction models, all contributing to overall asset sales.

"We are a dynamic, diverse and agile team that genuinely values mutual respect, learning, experimentation, and results!"


Aiming to harness the value of our operations team's immense collection of data is a huge business initiative, and the firm wants to hire a highly-skilled Data Scientist to drive innovation for future success. The role is senior level team member who is a deep thinker and will have a powerful voice in driving company growth. They live to create hypotheses, solve problems, and present any and all assumptions back to essential stakeholders by owning the solution from end to end. If freedom, autonomy and head scratching professional challenges rock your world, we could be a great match. Some responsibilities include:

  • Building prototype code for integration of new algorithms to exploratory analysis, construct relevant variables, and perform sample design
  • Defining data requirement to build complex predictive models to drastically improve business operations
  • Research and development for data-driven analysis on structured and unstructured data sets
  • Act as key consultant to recommend and develop innovative solutions
  • Analyzing large, complex data sets, solving problems using advanced statistical and Machine Learning techniques
  • Work collaboratively with engineering and product management teams to integrate new quantitative features and product enhancements


The successful Principal Data Scientist will likely have the following skills and experience:

  • MS or PhD degree (preferred) in Mathematics, Physics, Statistics, or Computer Science;
  • Applied Machine Learning experience on LARGE datasets, with commercial experience in building predictive models
  • Prior experience with advanced Mathematic and statistical modeling, and applying it to data mining methods (GLM/Regression, Trees, Clustering, SVM, Time Series analysis etc.)
  • FLUENT in Python and/or R, as well as SQL programming!
  • Skilled in data warehousing, cleaning/transforming data for future engineering, and leveraging visualization tools
  • You are highly team-oriented, focusing on COLLABORATION and INTELLECTUAL CURIOSITY
  • Strong verbal and written STORYTELLING abilities
  • Bonus: Mortgage or Real Estate experience!


A competitive base salary of $130,000 - $150,000 + Bonus +Flex PTO + 401k Match + Gym membership! + Flexible on remote work… + Education assistance!


Machine Learning| Python| Tableau| SQL| Data Science| Statistics| Mortgage | Real Estate | Trading

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New York
US$130000 - US$150000 per year + Bonus
  1. Permanent
  2. Data science

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Visit our Blogs & News portal or check out our recent posts below.

A Data Engineer is a Unique Blend of Data Professional

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The Harnham 2019 Data & Analytics Salary Guide Has Arrived

We are thrilled to announce the launch of our 2019 Data & Analytics Salary Guide. With over 1,500 respondents across the USA, this year’s guide is our largest and most insightful yet.  Looking at your responses, it is overwhelmingly clear that the Data & Analytics industry is continuing to thrive. This has led to an incredibly active market with 72% in the US willing to leave their role for the right opportunity.  Salary expectations remain high, although we’re seeing that candidates, on average, expect 10% more than they actually achieve when moving between roles.  We’ve also seen a change in the reasons people give for leaving a position, with a lack of career progression overtaking an uncompetitive salary as the main reason for seeking a change.   There also remains plenty of room for industry improvement when looking at gender parity; the US market is only 23% female, falling to 17% in Data Engineering roles and 16% in the Data Science space.  In addition to our findings, the guide also include insights into a variety of markets and recommendations for both those hiring, and those seeking a new role.  You can download your copy of the guide here.

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