The SOA-PAX Data Science team consists of highly skilled Data Scientists working together following an agile methodology and design thinking. We are a start-up department within SOA-PAX with driven and creative attitudes. We take the time to understand our internal and external client's needs and translate those into solutions that our clients can act upon. Our goal is to deliver innovative products that provide insight for Speech Analytic problems using Machine Learning, Deep Learning, and Natural Language Processing methods.

Responsibilities:

Perform hands-on data analysis and modeling with huge data sets
Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms
Work side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products
Discover data sources, get access to them, import them, clean them up, and make them model-ready
Create and refine features from the underlying data. Youll enjoy developing just enough subject matter expertise to have an intuition about what features might make your model perform better, and then youll lather, rinse and repeat
Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your optimizations and communicate results to peers and leaders
Explore new design or technology shifts in order to determine how they might connect with the customer benefits we wish to deliver

Qualifications:

B.S. or B.A. in Computer Science, Information Systems, Business Analytics, Mathematics, Statistics, Engineering, or a related technical field required
Advanced degree in Computer Science, Information Systems, Business Analytics, Mathematics, Statistics, Engineering, Business Administration or a related field preferred
3+ years of professional experience with applying quantitative research in optimizing human decisions using technologies like machine learning and/or deep learning
3+ years using major machine learning/deep learning frameworks (e.g., Scikit-learn, PyTorch, TensorFlow and Keras) and algorithms (e.g., CNN, GAN, LSTM, RNN, XGBOOST)
3+ years of data engineering experience with modern big data analytics architectures (Hadoop, SQL, HIVE, Spark, Snowflake, etc.) on major cloud platforms (e.g., AWS, Azure, Google Cloud)
3+ years programming skill in Python, Scala, Julia
Working knowledge with modern cloud-based data storage and compute environments
Experience deploying ML models into discovery/production environment to drive insights (e.g., CI/CD, test driven development, logging)
Experience with AWS services such as EC2 instances, Fargate, SageMaker, and Step Functions is a plus
Experience working in an agile delivery model is a plus
Demonstrated self-direction and willingness to learn new techniques
Ability to communicate complex ideas in a clear, precise, and actionable manner
Excellent communication and presentation skills, with the ability to articulate new ideas and concepts to technical and non-technical partners
PowerBI experience a plus

Essential Duties and Responsibilities:
- Apply advanced methods to analyze operational data and derive meaningful, actionable insights for stakeholders and business development partners.
- Serve as subject matter expert (SME) in the area of data and analytical product usage for peer analysts and operational stakeholders - particularly in the appropriate uses and limitations of statistical and analytical applications.
- Attain a high degree of knowledge about MAXIMUS data infrastructure.
- Design and develop data queries, cubes, etc. using data warehouse, business intelligence, and analytical products to fulfill ad-hoc data requests.
- Analyze extracted data, review for accuracy and look for trends.
- Provide insights and analyses around operations and project data.
- Participate in the data science product development review process, in particular implementing code review, testing, and data profiling of newly developed products.
- Develop and implement metrics, functions, and scripts as KPIs and in existing BI/Dashboards as needed.
- Inform operational partners on product performance as well as product usage trends.
- Consult with analytical leaders to understand current and future business goals and strategies, and ensure that methods and work products are aligned.
- Balance accuracy of analysis with needs for rapid response.
- Develop partnerships with technical peers and business partners.
- Perform other duties as assigned.

Minimum Requirements:
- Bachelor's degree with 3+ years of experience. Preferred fields of study include quantitative field such as Statistics, Mathematics, Operations Research, Economics, Computer Science, Machine Learning (or similar
- Ability to present data in a simple, clean, concise visual and written manner.
- Exposure to machine learning techniques and algorithms.
- Experience with common data science toolkits, such as R, Weka, Python/NumPy, MatLab, etc.
- Statistical experience and understanding of distributions, statistical testing, reGEDssion, etc.
- Proficiency in using query languages such as SQL and use of relational databases and SQL.
- Experience quantifying and prioritizing projects that require heavy data analysis.
- Experience working directly with business users and requirements documentation.
- A strong passion for empirical research and for answering complex questions with data.