Role Description As a Senior Data Scientist, you will play a pivotal role in our data science efforts, with responsibilities including, but not limited to, the following: - Advanced Analytics: Apply state-of-the-art data science techniques to analyze and extract meaningful insights from vast and diverse datasets. - Predictive Modeling: Develop and implement advanced predictive models to forecast key risk factors relevant to insurance and potentially other use cases. - Collaboration: Collaborate closely with our data engineers, product managers, and other business stakeholders to translate data insights into actionable strategies and solutions. - Data Visualization: Create compelling data visualizations and reports to communicate findings effectively to both technical and non-technical audiences. - Research and Innovation: Stay at the forefront of data science research, exploring new methodologies and technologies to drive innovation within the company. Qualifications - 3-5 years proven track record as a Data Scientist working with large datasets (e.g., millions of rows), from prototyping to business impact, analytics and ML use cases. - Deep understanding of machine learning and statistical methods with their underlying theory and math. - Demonstrated experience in building, deploying, and showing business value from predictive models and data products. - Highly proficient in Python. - Proficiency in SQL databases, understanding schemas, and data types. - Real-world experience with at least one distributed data platform (preferably Spark). - Solid software development experience, including translating ML models into production software, especially in collaboration with other engineers. - MS or PhD in a quantitative discipline, especially Statistics, Math, or similar. - Strong communication skills. Requirements - Deep Learning, especially Transformers. - Experience with GLMs, including for actuarial frequency applications. - Boosting algorithms (CatBoost, XGBoost, etc.). - Experience with distributed machine-learning frameworks, like Spark, etc. - Creating data pipelines for analytics or ML applications. - Experience using AWS (EC2, EMR, S3, etc.) or similar cloud provider (Google, Azure, etc.). - Resourceful self-starter and team player with strong leadership skills. - Uncompromising attention to details. - Proven ability to be creative and resourceful in a fast-paced, entrepreneurial environment. - Must be comfortable working independently. - React well and quickly to frequent project demands and requirement changes. - Excellent analytical, troubleshooting, and problem-solving skills. - Strong written and communication skills and positive attitude working with customers and partners.

Role Description We are looking for an Analytics PM / Virtual Assistant to support cross-functional teams by building and maintaining Salesforce dashboards, reports, and operational analytics. The role will focus on delivering real-time visibility into key business metrics for stakeholders including GVCC, Customer Success Managers (CSMs), and network operations teams. This is a contract-based role ideal for someone who is highly organized, analytical, proactive, and comfortable working with large datasets and stakeholder requests in a fast-paced environment. Key Responsibilities - Salesforce Reporting & Dashboard Management - Design, build, and maintain Salesforce dashboards and reports for operational and executive visibility. - Create automated reporting workflows and scheduled reports. - Develop KPI tracking dashboards for: - Customer success metrics - Ticket resolution performance - Network operations health - SLA adherence - Escalation trends - Revenue and account activity - Ensure dashboard accuracy, consistency, and usability across teams. - Analytics & Data Insights - Analyze operational and customer data to identify trends, bottlenecks, and improvement opportunities. - Convert raw data into actionable insights for leadership and operations teams. - Prepare weekly/monthly business review reports and presentations. - Support ad hoc data analysis requests from stakeholders. Company Description Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US.

Role Description We are seeking an experienced Senior Data Science & Machine Learning Engineer to design, build, and deploy scalable data-driven and AI-powered solutions. - 5+ years of experience in Data Engineering, Machine Learning Engineering, or related fields. - Strong programming expertise in Python (Pandas, NumPy, PySpark, etc.). - Design, develop, deploy, and maintain production-ready Machine Learning models. - Experience with ML model training, deployment, monitoring, and observability. - Hands-on experience with Deep Learning frameworks such as TensorFlow and PyTorch. - Build robust data pipelines, feature engineering workflows, and experimentation platforms. - Experience working with LLMs, Generative AI, MLOps, and modern AI architectures. - Familiarity with CI/CD pipelines, Git, and software engineering best practices. - Ability to mentor junior engineers and contribute to technical design decisions. Qualifications - Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or related field. - Master's degree or PhD is a plus. - Strong analytical, problem-solving, and communication skills. Company Description

Role Description The Senior Data Scientist at RGA plays a pivotal role in pioneering advanced machine learning (ML) and generative AI (GenAI) solutions that drive innovation in the insurance and reinsurance industry. Leveraging deep technical expertise, this leader independently architects and implements sophisticated analytical models to solve high-impact business challenges, powering RGA’s data-driven transformation. - End-to-End Modeling: Design, develop, and deploy sophisticated machine learning models that address mission-critical business challenges, including underwriting automation, pricing optimization, and claims analytics. - GenAI Solution Development: Lead the end-to-end development and implementation of generative AI solutions, leveraging large language models (LLMs) for advanced document processing and automated content creation. - Technical Leadership: Serve as a technical authority and mentor for colleagues, providing expert guidance on best practices in machine learning modeling and solution architecture. - Project Leadership: Lead and manage small-scale projects, including defining scope and objectives, developing project plans, and coordinating activities across cross-functional teams. - Data Pipeline Architecture: Architect, develop, and maintain robust, automated data pipelines and ETL processes in partnership with data engineering teams. - Stakeholder Communication: Effectively communicate complex analytical findings and actionable recommendations to a wide range of stakeholders. - Model Governance: Champion and enforce rigorous model governance practices by conducting thorough model validation and ongoing monitoring. Qualifications - Bachelor's or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field; OR a Bachelor's degree with equivalent experience. - 5-7 years of progressive experience in data science and machine learning. - Quantitative Skills: Demonstrates a deep understanding of advanced statistical techniques and applies a broad range of machine learning algorithms. - Technical Skills: Possesses advanced proficiency in Python and/or R, and skilled in using modern ML and GenAI frameworks. - GenAI Expertise: Hands-on experience implementing GenAI technologies, including large language models (LLMs) for natural language processing. - Data Management: Expertise in using SQL for querying, transforming, and aggregating data from relational databases. - Problem-Solving: Exhibits excellent problem-solving skills and approaches challenges creatively and analytically. - Communication: Effectively communicates difficult or sensitive information to diverse stakeholders. - Leadership: Serves as a force multiplier for the team by mentoring junior members and sharing best practices. - Business Acumen: Demonstrates a strong understanding of key business drivers and applies data science expertise to identify opportunities for improvement. Requirements - Ph.D. in a related quantitative field (preferred). - Experience in the life/health insurance or reinsurance industry (preferred). - Experience working with Databricks, Snowflake, and AWS tech stacks (preferred). - Experience working with large longitudinal datasets using actuarial methods of analysis (preferred). Benefits - Gain valuable knowledge from and experience with diverse, caring colleagues around the world. - Enjoy a respectful, welcoming environment that fosters individuality and encourages pioneering thought. - Join the bright and creative minds of RGA, and experience vast, endless career potential. Compensation Range $126,710.00 - $188,840.00 Annual. Base pay varies depending on job-related knowledge, skills, experience and market location. In addition, RGA provides an annual bonus plan that includes all roles and some positions are eligible for participation in our long-term equity incentive plan. RGA also maintains a full range of health, retirement, and other employee benefits. Company Description RGA is a purpose-driven organization working to solve today’s challenges through innovation and collaboration. A Fortune 200 Company and listed among its World’s Most Admired Companies, we’re the only global reinsurance company to focus primarily on life- and health-related solutions.