Fundstreet Technologies is looking for a seasoned Data Scientist to join our Analytics team. This role will be responsible for using advanced statistical and machine learning techniques to drive business processes. You will work closely with business stakeholders to understand business challenges and propose streamlined solutions. You will lead the charge in A/B testing within the organization and design experiments to prove success. You will perform EDA, create ETL processes, construct robust dashboards and reports, and highlight opportunities for change.
We want to work with high performing badasses that will play an integral part in our expansion of the company. We understand one thing: it all comes down to working with the right people and enabling them to do what they do best.
Main Responsibilities
- Utilize advanced statistical and machine learning techniques to analyze large datasets and identify patterns and trends. Conduct exploratory data analysis, feature engineering, and data preprocessing for machine learning.
- Facilitate the deployment and governance of machine learning models for real-time and batch processing.
- Perform model evaluation and validation on a regular basis to ensure robust performance.
- Engineer A/B tests with scientific rigor. Gather test data and validate results to present to business stakeholders.
- Produce statistical and data analysis visuals (charts, infographics) to communicate findings clearly and effectively to a non-technical audience.
- Collaborate with team members, product managers, and business stakeholders to identify opportunities for new and innovative data solutions.
- Keep up to date with the most recent developments and improvements in the data and machine learning space. Always be learning and improving skills.
- Analysis areas might include, but are not limited to: marketing segmentation, text mining, sentiment analysis, time series forecasting, credit risk modeling, and risk based pricing models.
Requirements
- Bachelor’s degree in mathematics, statistics, computer science, or data science.
- Proficiency in data manipulation. Excellent SQL and Python skills for data wrangling and ETL.
- Experience with dashboard tools such as PowerBI.
- Experience building credit or risk models for Financial Services, Lending, or Insurance.
- Well rounded data science skillset – Exploratory Data Analysis, Feature Engineering, Fitting, Tuning, and Comparing models.
- Experience with statistical modeling and data analysis using programming languages such as Python.
- Experience in ML engineering, cloud-based deployment, and machine learning model lifecycle management.
Benefits
- Hybrid Position (3 days in office 2 remote).
- Local & National Health Insurance
- Dental and Vision insurance
- Group Medical Bridge
- Supplemental Insurance through Colonial
- 401k with Match
- Gas Stipend
- ID Protection: 100% covered by the company
- Life Insurance: 100% covered by the company
- PTO
- 6 Paid Holidays