What are the responsibilities and job description for the Data Scientist position at ARGO?
ARGO is a leading provider of software and analytics solutions for both the financial services and healthcare industries. ARGO transforms business processes for financial service providers and healthcare organizations using proven business models and software innovation informed by real customer challenges, breakthrough technology, and rich analytics.
We are looking to add a Data Scientist with mathematician/statistician and computer science knowledge/experience test that will work within the data science team in developing, evaluating and implementing advanced algorithms for classification, clustering, data reduction, sampling and optimization based on statistical models to power ARGO analytical solutions. This person should also be able to execute robust models for automating various aspects of the data analysis process, including getting customer data, running analytics, and building value-add models for delivery to a production environment.
A key to success in this position will be innovation in the data science space while tying project outcomes to the broader goals of the organization and improvement of the product offering.
WHAT WE ARE LOOKING FOR:
- 3 years post-academic and/or recent industry experience in model development and statistical analysis of large datasets
- Proven ability to balance probability and statistical theory and algorithms science with pragmatic problem solving skills
- A track record of developing and applying advanced predictive algorithms and behavioral models to solve real world problems
- Experience using statistical computer languages (Python, R, SQL, etc.) and machine learning methods to manipulate data and draw insights from large data sets
- Working Knowledge of:
- Determination of structure or distribution of data
- Common classification techniques
- Common regression techniques
- Predictive modeling
- Experience with distributed data/computing tools
- Experience visualizing/presenting descriptive statistical data with modern visual tools (i.e.: MS Power BI)
- Strong communication skills, both verbally and written, and the ability to develop and present proposals, results and business cases to internal and customer executives
- Experience in commercial software development lifecycle (SDLC) methods
WHAT YOU WILL DO:
- Work on projects developing, evaluating, and implementing analytical models
- Support the adoption of data science and well improved analytics across the whole organization
- Analyze data to produce and improve statistical, mathematical, or machine learning models or algorithms to forecast results for ARGO’s predictive analytics products
- Build and maintain a reliable, efficient workflow to ingest, store, and analyze data sets
- Mentor and assist engineers in creating and deploying production ready models
- Define and collect metrics for key performance indicators (KPI) to assess the effectiveness and accuracy of models both during analysis and in production
- Document and explain models, algorithms, and their KPIs to internal and external stakeholders
EDUCATIONAL REQUIREMENTS:
The candidate will have a Bachelor degree (Master’s is a plus) in Statistics, Applied Math, Machine Learning, Physics, Econometrics or a similar quantitative field with focus and depth in mathematical algorithms, probability theory, statistical modeling, and machine learning.
ADDITIONAL REQUIREMENTS:
Applicants for U.S. or Canadian based positions with ARGO must be legally authorized to work in the United States or Canada. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is not available for any ARGO positions.
PHYSICAL DEMANDS:
While performing the duties of this job, the employee is regularly required to stand; walk; sit; use hands to finger, handle, or feel; reach with hands and arms; talk or hear. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus.