• Diseñar, evaluar y monitorear agentes inteligentes y modelos de Machine Learning / Generative AI • Desarrollar modelos supervisados y no supervisados usando Python • Construir y mantener pipelines de experimentación, flujos de validación y procesos de implementación • Operar modelos de producción a través de Azure Machine Learning

Role Description This role offers a unique opportunity to lead advanced data science initiatives in the manufacturing domain, driving measurable improvements across production, operations, and supply chain processes. You will work on end-to-end data solutions, from integrating industrial systems and extracting real-time data to building predictive models and delivering actionable insights. The position blends hands-on engineering with strategic problem solving, allowing you to influence operational efficiency and decision-making at scale. Ideal candidates are skilled in cloud-based data pipelines, machine learning, and industrial protocols, and can communicate complex analyses effectively to both technical teams and executive stakeholders. You will collaborate across remote, global teams in a dynamic, innovative environment that values impact, learning, and cross-functional expertise. - Lead the development and deployment of predictive models for maintenance, anomaly detection, demand forecasting, and process optimization in manufacturing settings - Build and optimize scalable cloud data pipelines for high-volume IoT and operational data using tools like Spark, Kafka, Airflow, and Delta Lake - Integrate OT and IT systems including MES, SCADA, and ERP for real-time data extraction and analysis using industrial protocols such as OPC-UA, MQTT, and Modbus - Apply statistical methods, Six Sigma, SPC, OEE, and lean methodologies to drive measurable gains in yield, uptime, and efficiency - Translate complex model outputs into actionable insights and recommendations for operations and executive stakeholders - Design and execute experiments and simulations to validate process improvements and quantify business impact - Collaborate with cross-functional teams to ensure solutions align with business objectives and operational realities Qualifications - 8–10 years of overall data science experience with 2–4 years in the manufacturing domain - Strong proficiency in SQL and Python, with hands-on experience in medallion/lakehouse architectures on platforms like Databricks, Snowflake, AWS, or Azure - Proven experience in building, deploying, and operationalizing ML models in industrial environments using scikit-learn, TensorFlow, or PyTorch - Deep understanding of industrial operations, production planning, and systems (MES, SCADA, ERP) - Expertise in data engineering, cloud data pipelines, and IoT data integration - Solid grounding in statistical methods: time series analysis, regression, clustering, hypothesis testing - Strong communication skills with the ability to convey technical insights to non-technical stakeholders - Experience designing A/B experiments and process simulations to evaluate business impact - Adaptable, collaborative, and capable of working in a fast-paced, remote, and cross-functional environment Benefits - Opportunity to work on cutting-edge data science projects in manufacturing and industrial operations - Remote work with occasional travel across the United States - Exposure to high-impact, enterprise-scale industrial data environments - Collaborative, innovative, and non-hierarchical work culture - Professional growth opportunities through hands-on experience with advanced ML and data engineering - Competitive contract-to-hire compensation

Role Description The Computer Scientist (Journeyman) supports the research, design, and development of software-based analytical solutions. This role focuses on applying computer and information science principles to solve complex data, modeling, or system challenges. Qualifications - Bachelor’s degree (BA/BS) in Computer Science or a related field - 3–15 years of professional experience in software development, systems engineering, or applied computer science Requirements - U.S. citizenship - Ability to obtain and maintain a Tier 3 investigation - Experience working in secure or regulated environments preferred Benefits - Health insurance - Dental insurance - Vision insurance - Life Insurance - 401(k) Retirement Plan with matching - Paid Time Off - Paid Federal Holidays

Role Description Quanticate is seeking an experienced Clinical Data Project Manager to lead and manage complex data management projects across the clinical development lifecycle. This is your opportunity to bring strategic insight and operational leadership to a role that directly supports the success of our global pharmaceutical and biotech partners. As a Clinical Data Project Manager at Quanticate, you’ll take ownership of high-value clinical data projects, driving delivery excellence and regulatory compliance from start to finish. If you thrive on leadership, precision, and strategic impact, we want to hear from you. - Lead full lifecycle project management from data setup to database lock - Ensure successful delivery of CDM activities to time, budget, and regulatory standards (ICH-GCP) - Act as the primary liaison for clients—managing communication, escalations, and expectations - Drive operational excellence, process consistency, and team productivity across global CDM projects - Manage budgets, scope changes, risk mitigation, and resource allocation - Represent Quanticate at client meetings, audits, and conferences - Assist on bid defences with clients Qualifications - Degree in Life Sciences or similar (or equivalent experience) - Strong experience in Clinical Data Management, including CRO experience - Demonstrated success in leading complex global CDM projects - Deep knowledge of EDC systems (e.g. Rave, Medrio, Veeva) and tools like RTSM, ePRO, and tSDV - Strong expertise in project financials, reporting, and cross-functional collaboration - Comfortable representing CDM in external audits and contributing to continuous improvement initiatives Benefits - Salary based on experience - 20 days annual leave - Monthly allowance for employees working from home - Flexible working hours to support a healthy work/life balance - Medical insurance paid for each employee - 7.5% contribution towards an employee’s retirement annuity plan - Recognition gifts for long service (5th, 10th, 15th, or 20th anniversary)