Senior Data Scientist at CAI in Pennsylvania

Senior Data Scientist Location: PA-CLIENT-STATE Senior Data Scientist Req number: R7619 Employment type: Full time Worksite flexibility: Remote Who we are CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise. Job Summary As a Senior Data Scientist, you will create ETL workflows, scripts, statistical models, and visualizations while taking responsibility for the design, build, test, execution, and support of data migration, cleansing, wrangling, etc. The ideal candidate will have a detailed understanding of the underlying data and data structures of multiple systems to allow in depth analysis of existing and potential data insights. Job Description We’re looking for a seasoned Senior Data Scientist to lead machine learning initiatives, guide a high‑performing team, and deliver impactful insights across the organization. This role blends hands‑on modeling, data engineering, and strategic leadership. You will create ETL workflows, scripts, statistical models, and visualizations while taking responsibility for the design, build, test, execution, and support of data migration, cleansing, wrangling, etc. This position is contract and remote (or onsite in Novi, Michigan).  Only work authorizations that will not require sponsorship now or in the future will be considered. What You’ll Do Data Modeling: Selecting features, building and optimizing classifiers using machine learning techniques Execute machine learning projects using state-of-the-art methods Extending company’s data with third party sources of information when needed Creating automated anomaly detection systems and constant tracking of its performance Data Manipulation: Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Collect data from a wide variety of corporate databases, including various SQL databases -Microsoft, Redshift, Teradata, Oracle, Netezza, etc.-, Access, Excel, plain or formatted text files, OLAP cubes –Microsoft, Oracle-, and no-SQL databases Parse data out of poorly structured XML and invalid HTML documents Use regular expressions to extract information from un-structured text documents Deal with missing data through multiple-imputation or the use of advanced models and automate repetitive tasks using scripts Data Organization: Build effective, reliable, and robust ETL processes that govern the data ingestion flow Design database models, consistent table structures, and advanced dimensional schemas that carry out data quality and consistency standards Apply modeling approaches, business intelligence patterns, and data management techniques Data Analysis: Demonstrate advanced SQL skills, such as CTEs and window functions, to work with extensive amounts of data at various aggregation levels Review and analyze legacy code/scripts to understand data processing logic and business rules Ability to apply statistical learning languages to build predictive models that enrich, expand, and allow deeper understanding of data analyses and solutions Distributed systems knowledge, specifically of HDFS and the Hadoop ecosystem Data Visualization: Communicate complex technical findings to non‑technical and executive audiences by using interactive data‑visualization tools (e.g., Tableau, Power BI) to craft clear, compelling stories through charts and dashboards What You’ll Need Required: 7+ years in infrastructure or application operations building production ready Machine Learning models in Python 5+ years leading Data Science teams and managing resources 5+ years building end-to-end data science or analytics pipelines in cloud environments Proficiency in Python, PySpark, R, JavaScript, C#, or similar languages Advanced SQL skills Experience using Tableau or Power BI Familiarity with at least one ETL tool (Alteryx, KNIME, SSIS, Pentaho, DataStage, etc.) Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Understanding of cloud architecture Ability to synthesize and translate stakeholder requests into actionable solutions Creative, practical problem-solving mindset Strong motivation to learn new analytical techniques and tools Excellent verbal and written communication skills Experience supporting both Waterfall and Agile development methodologies Ability to work effectively across cross functional and cross technology teams Preferred: Knowledge in Azure, AWS or GCP is desired Degree in Data Science/Statistics, Computer Science, Engineering, or similar Physical Demands Ability to safely and successfully perform the essential job functions consistent with the ADA and other federal, state and local standards Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc. Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard and monitor #LI-AE1 Reasonable accommodation statement If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111. $85.00 - $100.00 per hour The pay range for this position is listed above. Exact compensation may vary based on several factors, including location, experience, and education. Benefit packages include medical, dental, and vision insurance, as well as 401k retirement account access. Employees in this role may also be entitled to paid sick leave and/or other paid time off as provided by applicable law.