Role Description We're hiring a Lead Data Scientist to own the technical roadmap for the ML and GenAI capabilities powering our next-generation retail and analytics platform — from price optimization and demand forecasting to promotion effectiveness and AI-driven copilots. You'll set the technical bar for the data science organization and lead a distributed team, including our Poland-based data scientists. - Own the technical roadmap for ML/AI models powering price optimization, demand forecasting, promotion effectiveness, and markdown recommendations. - Architect and lead development of GenAI-powered agents and copilots (e.g., pricing copilots, demand intelligence agents) in partnership with engineering and product. - Set technical standards for model development, validation, and MLOps across the data science organization. - Mentor, coach, and grow a distributed team of data scientists, including direct oversight of the China and Poland-based team. - Partner with product and engineering leadership to translate retail and trade-promotion business problems into Data Science solutions. - Make build-vs-buy calls on LLM/GenAI tooling and vendor platforms together with ENG. - Present model performance, technical roadmap, and AI strategy to executive leadership and, where relevant, customers and prospects. - Track emerging AI/ML techniques and assess their applicability to retail and CPG use cases. - Develop scalable feature engineering workflows over large retail datasets. Qualifications - 7+ years of experience in data science or applied ML, including 2+ years leading data scientists or a technical team. - Proven track record shipping production ML models at scale. - Experience designing, building, and shipping models for price elasticity, demand forecasting, promotion effectiveness, and similar retail/CPG use cases. - Strong communication skills — able to translate technical work into business impact for executives and customers. Requirements - Proficiency in Python, SQL, and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). - Familiarity with GenAI frameworks (e.g., LLMs, Dify, LangChain, RAG pipelines). - Familiarity with cloud-based data platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop, Databricks). - Experience with data visualization tools (e.g., Power BI, Tableau) and modern MLOps practices.

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