Job Description

Data Scientist Req number: R5301 Employment type: Full time Worksite flexibility: Remote Who we are CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 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 We are seeking Data Scientist with expertise in analytical modeling, ML methodologies, and data visualization to elevate our data-driven culture and deliver actionable insights that optimize business performance. The candidate must have proven success in coalescing, analyzing, synthesizing and contextualizing complex data sets (qualitative and quantitative) to deliver metrics, insights, advanced machine learning / AI analytics, with actionable recommendations that have a direct impact on business strategy and inform customer experience decisions. This is a Full-time and Remote position. Job Description What You’ll Do Understand current state architecture, including pain points. Translate Business/Customer Problems: Partner with the Customer Understanding Manager to translate business/customer challenges into data-driven hypotheses, insights, and recommendations that optimize marketing and sales performance. Insight Generation: Demonstrated experience proactively identifying and generating insights to enhance business and marketing performance, moving beyond descriptive analysis to inform strategic decisions. Storytelling with Data: Strong data analytics, visualization, and storytelling skills along with great attention to details. Modeling & Advanced Analytics: Develop and manage customer health programs, leveraging predictive analytics and machine learning models to assess customer engagement, churn risk, and growth potential. Quantify Impact of Marketing Initiatives: Perform deep-dive statistical analysis to quantify the impact of marketing initiatives on business KPIs, including revenue growth, retention rates, and customer lifetime value. Develop NPS Analysis: Support development of NPS (Net Promoter Score) analysis. Identify relevant data from internal and external sources to align NPS score to operational, financial, and experience metrics. Design and Maintain Automated Dashboards: Design and maintain automated dashboards and self-service analytics tools using Salesforce, Tableau, and Power BI to support real-time decision-making. Apply AI/ML methodologies: Utilize AL/ML techniques such as predictive modeling, clustering, key driver analysis, and NLP to uncover customer trends and improve engagement strategies. Promote Insight-Informed and Data-Driven Culture: Develop regular reports, executive briefs, and blogs to reveal market, industry, and customer trends, fostering an insight-informed and data-driven culture within the company. Develop Scorecards and Performance Dashboards: Lead the creation of scorecards and performance dashboards, ensuring marketing and sales teams have the insights needed to optimize decision-making. Drive Innovation in Data Strategy: Stay updated on evolving AI/ML methodologies, automation frameworks, and analytics best practices to drive innovation in data strategy. Experimental Design & Statistical Modeling (hierarchical linear models, regression analysis, hypothesis testing, significance testing). AI/ML Expertise (GenAI, NLP, tree-based models, deep learning, ModelOps/MLOps best practices, reinforcement learning). Data Engineering & Processing (structured/unstructured data manipulation, building ETL pipelines, Python libraries: pandas, scikit-learn, statsmodels, etc.). Data Storytelling & Visualization (Tableau, Power BI, Salesforce, Plotly, Adobe Analytics, etc.). Automated Analytics & Cloud Computing (AWS, GCP, Azure, Databricks, Snowflake, BigQuery). Strong time management and organizational skills with the ability to prioritize and execute projects independently. What You'll Need Bachelor’s degree in quantitative discipline: computer science, Statistics, Applied Mathematics, Economics, or a related field . 5-7 years of experience in advanced analytics, data science, or marketing intelligence , preferably in B2B or manufacturing industries. 4+ years Tableau experience. 4+ years of SQL development skills writing queries, transforming data, mining structured and unstructured data. Strong expertise in SQL, Python, and statistical modeling , with experience in building scalable data pipelines . Proficiency in data visualization and self-service analytics tools (Tableau, Power BI, Salesforce Analytics, etc.). Hands-on experience with AI/ML frameworks, NLP, and MLOps best practices Proven ability to synthesize complex data sets into strategic business insights that drive measurable outcomes . Strong communication skills, with the ability to translate complex technical findings into actionable business recommendations . Expert at hypothesis generation , creating data-driven business questions and experimental design techniques. Agile project management skills with the ability to manage multiple priorities and deliver high-impact results . Passion for continuous learning, research, and innovation in data analytics and AI. Physical Demands This role involves mostly sedentary work, with occasional movement around the office to attend meetings, etc. Ability to perform repetitive tasks on a computer, using a mouse, keyboard, and monitor. 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.