Responsibilities
- Develop and support cloud-based AI applications and tools utilizing cutting-edge open-source
and cloud technologies. This position leads and/or participates in all phases of the project
lifecycle, including research, requirements gathering, database development, cloud-based
application development, analytical report creation.
- Explain and defend potential insights and conclusions drawn from data, as well as identify and
investigate potential data anomalies to determine root cause and recommend corrective action.
- Display and visualize processed information so its value can be understood.
- Apply exploratory or predictive analytics to solve business problems.
- Performs data modeling. Implement and test data modeling designs. Use advanced math and
statistics. Use modern data analytical techniques working with information retrieval, machine
learning, matrix and graph algorithms, unsupervised clustering & data mining to solve business
problems.
- Work with big datasets with minimal engineering support.
- Integrate research and best practices into problem avoidance and continuous improvement.
Exercise independent judgment in methods, techniques, and evaluation criteria for obtaining
results.
- Lead a small team and/or project. Mentor junior data scientists
- Work effectively both as an individual analytic contributor and collaborator within the team
Minimum Qualifications
- 3+ years of industry experience in statistical modeling, data science, and analysis
- Experience with common supervised learning techniques to include but are not limited to
regression models such as logistic and linear regression, classification models such as decision
trees, naive bases, nearest neighbor, random forest, and neural network models, and
unsupervised learning technique such as k-means clustering. Use case may include but are not
limited to forecasting, time series modeling, and discovering the causal effect relationship
between variables using propensity score analysis, inverse probability weighting, path analysis,
structural equation modeling and Bayesian networks, or building recommendation system by
using collaborative filtering and content-based filtering techniques
- Hands-on experience developing and deploying statistical and ML models
- Experience writing code in Python with documentation for reproducibility
- Experience handling large datasets in different formats, diving into data to discover hidden patterns, using data visualization tools, writing SQL
- Must have exceptional analytical, conceptual, and problem-solving abilities with a results- focused mindset
- Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations
- Must have excellent written and oral communication/presentation skills
- Must have a strong interest in/understanding of governance industry trends, challenges, opportunities.
- Must have the ability to translate business requirements into critical data dependencies and requirements