Principal Data Scientist

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

THE COMPANY

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!"

THE ROLE

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

YOUR SKILLS AND EXPERIENCE

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!

THE BENEFITS

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

KEYWORDS

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

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58382
New York
US$130000 - US$150000 per year + Bonus
  1. Permanent
  2. Data science

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Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

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

A Data Engineer is a Unique Blend of Data Professional

From startup and small business to large enterprises, each type of business requires a unique blend of Data professional. Though in today’s world, much of the Data being gathered, catalogued, and analyzed happens both in the Cloud and on a hard drive, each type of business has a different need, budget, goals, and objectives. But there is one thing each and every business will have in common. At the heart of the Data team will be a Data Engineer. The Three Main Roles of a Data Engineer This is an analytics role in high demand. It is a growing and lucrative field with steps and stages for nearly every level of business and education experience. For example, a Data Scientist interested in stepping into a Data Engineer role might begin as a Generalist. In all, there are three main roles for each level and type of business – Generalist, Pipeline-Centric, and Data-Centric. Let’s take a quick look at each of the roles with an eye toward the type of person who might be the best fit: Generalist – Most often found on a small team, this type of Data Engineer is most likely the only Data-focused person in the company. They may have to do everything from build the system to analyze it, and while it carries its own unique set of skills, it doesn’t require heavy architecture knowledge as smaller companies may not yet be focusing on scale. In a nutshell, this might be a good entry point for a Data Scientist interested in upskilling and reskilling themselves to transition into a Data Engineering role.Pipeline-centric – This focus requires more in-depth knowledge working with more complex Data science needs. This type of role is found more often in mid-sized companies as they grow and incorporate a team of Data professionals to help analyze and offer actionable insight for the business. In a nutshell, this role creates a useful format for analysts to gather, collect, and analyze each bit of Data at each stage of development.Database-centric – This role is found most often in larger companies and deals not only with Data warehouses, but is focused on setting up analytics databases. Though there are some elements of the pipeline, this is more fine-tuned. In a nutshell, this role deals with many analysts across a wide distribution of databases. A Fine Balance Between Technical Skills, Soft Skills, and Business Acumen While it’s important for anyone filing this role to have deep knowledge of database design as well as a variety of programming languages, its equally important to understand company objectives. In other words, once the groundwork is laid and the datasets established, it’ll be important to explain what it is the business executives need to know to make the best decisions for their business.  Knowing how and what to communicate to executives, stakeholders, and your Data team also means understanding how to best retrieve and optimize the information for reporting. Depending on your organization’s size, you may need both a Data Analyst or Scientist and a Data Engineer. Though this is less likely in medium and larger enterprises. On the flip side, in order to understand the business’ needs, you’ll also need to be good at creating reliable pipelines, architecting systems and Data stores, and collaborating with your Data Science team to build the right solutions. Each of these skills are meant to help you understand concepts to build real-world systems no matter the size of your business. One Final Thought… Do you like to build things? Tweak systems? Take things apart and see how they work, then put them back together better and more efficient than before? Then Data Engineering might be for you. Are you a business who knows you’re ready to scale up and hire a Data professional? We have a strong candidate pool and may have just the person you need to fill your role. Are you a candidate looking for a role in big Data and analytics? We specialize in junior and senior roles. Check out our current vacancies or contact one of our recruitment consultants to learn more.  For our West Coast Team, call (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com.

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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