Data Scientist

Data Scientist

Millions of people are looking to improve their lives through home ownership and smart usage of lending products like mortgages - but the whole process is confusing, opaque and reduced down to choosing the lowest rate and monthly payment. Meanwhile, most lenders aren’t helping their existing or potential borrowers through education and guidance the way they should.

We are changing this relationship! Hundreds of leading lenders rely on award-winning technologies from TrustEngine to build lasting borrower relationships that maximize lifetime customer value for the lender and empower the borrower. We are reimagining the lending and financial space by connecting borrowers with the right loan at the right time. Our team is always on the lookout for passionate and hardworking members who can help take us to the next level in helping borrowers achieve their goals.



About the Role:

If you're driven by a passion for data, obsess over driving change using data and have a desire to exceed expectations, we want to hear from you.

We are seeking a talented and motivated individual to join our team as our first Data Scientist. This is an exciting opportunity to shape the future of TrustEngine by driving data-driven decision making processes through developing advanced machine learning models that push the boundaries of what's possible in the fintech field. All with the goal of contributing towards our overall mission of allowing each home owner to achieve personal financial freedom.

You’ll be a solo data scientist, but you’ll be surrounded by a team that is passionate about delivering change with data and continuously reaching new levels of learning and quality to support the overall business. In addition, you’ll be reporting to the Director of Data, who has expertise in data science & analytics, plus a passion for scaling data teams by growing each team member individually and as part of the whole.

We work fast and agile, so flexibility and incrementality is a key mindset for this role. Move fast, be imperfect, but be honest about the imperfection as we get better. Your data acumen will be used to communicate the value our business delivers and you’ll continuously have a chance to one-up yourself.


As our first Data Scientist, you will be responsible for:

Data Analysis and Exploration:

Collect, clean, and process data from various sources to create derivative datasets.

Perform exploratory data analysis to identify trends, patterns, and insights that can drive business decisions. Partner directly with product and business team leads to continuously display results, receive feedback and iterate.


Model Development:

Build predictive and machine learning models to solve specific business problems, such as customer segmentation, scoring models, identify high performing creatives or recommendation systems. Write code to effectively process, and combine data sources in unique and useful ways, often resulting in analytics datasets that are easily used by the broader team. Work with engineering to productionize these datasets.


Data Visualization:

Create informative data visualizations and reports to communicate findings and insights to non-technical stakeholders. Synthesize data learnings into compelling stories and communicate them.


Collaboration:

Collaborate with cross-functional teams, including Customer Success, Sales, Marketing and Leadership, to identify data-driven opportunities and solutions. Act as a subject matter expert on data-related matters and provide guidance to the team.


Continuous Learning:

Stay up-to-date with the latest advancements in data science, machine learning, and fintech industry trends. Experiment with new techniques and tools to improve the effectiveness of data-driven initiatives.



Why join TrustEngine?

As a fully remote organization, we find creative and efficient ways to stay connected with each other while providing employees the autonomy to get their work done in the best way that fits their lifestyle. Whether you need to take time off to be with your family or go to a doctor’s appointment, we don’t micromanage your time as long as you’re getting your work done and meeting your goals.

We are an open organization and welcome honest feedback from our employees. Managers meet with their teams on a one-on-one basis every week to review projects and discuss concerns or roadblocks. Both sides have the freedom to share feedback.

Education:

  • Bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative discipline. Master’s degree is a bonus.


Technical Skills

  • Proficiency in programming languages is crucial. Should be skilled in languages such as Python or R, as they are commonly used for data manipulation, analysis, and machine learning.
  • Strong skills in data manipulation libraries (e.g., Pandas for Python, dplyr for R) and statistical analysis tools are essential.
  • Knowledge of machine learning algorithms and techniques, including supervised and unsupervised learning, regression, classification, clustering, and deep learning.
  • Proficiency in data visualization tools such as Matplotlib, Seaborn, ggplot2, or Tableau to create meaningful visualizations.
  • Understanding of databases and SQL for data extraction and manipulation, including familiarity with both relational and NoSQL databases.
  • Knowledge of big data technologies such as Hadoop, Spark, or NoSQL databases like MongoDB can be beneficial.
  • Familiarity with version control systems like Git to collaborate on code with other team members.


Soft Skills:

  • Analytical Thinking: The ability to analyze complex problems, break them down into manageable components, and develop data-driven solutions.
  • Problem-Solving: Strong problem-solving skills are essential to identify and address challenges in data and models.
  • Communication: Effective communication skills, including the ability to translate complex findings into non-technical language for stakeholders.
  • Teamwork: The ability to work effectively with colleagues from different backgrounds and collaborate on solutions is important.
  • Continuous Learning: Data science is a rapidly evolving field. You should have a commitment to staying up-to-date with the latest trends and techniques.
  • Business Acumen: Understanding the business context and being able to align data-driven insights with organizational goals.

Our benefits include but are not limited to the following: 100% company paid medical; company matching 401(k), paid maternity and paternity leave, unlimited FTO package, ongoing professional development and certification opportunities, competitive salary, special employee discounts and health and wellness perks.

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