Data Instructor Jobs

About the Role N26 is seeking an analytical, regulatory-minded Complaints Compliance & Prevention Manager to lead compliance governance, audit remediation, and the preventive control framework within our Complaints Management & Prevention department. Reporting directly to the head of the department, you will own the end-to-end planning and execution of our regulatory remediation roadmap, separating administrative control and preventive functions from operational case handling. In this role, you will establish a robust, BaFin-compliant preventive Root Cause Analysis (RCA) framework and oversee CMP's Written Orders (SfO) to ensure full operational integrity, data quality, and compliance across all active N26 markets.The role combines a compliance mindset with deep understanding of operations specificity. What You Will Do Regulatory Remediation & Governance: Lead the end-to-end delivery of the regulatory remediation roadmap, managing Test of Design (ToD) and Test of Effectiveness (ToE) milestones in alignment with BaFin MaBeschwer, MaComp, MaRisk, and general KWG expectations. Preventive Framework & RCA: Build, govern, and scale the preventive RCA framework (MaBeschwer Tz. 18), establishing risk-based selection triggers beyond volume (e.g., PSD2, WpHG, financial loss, reputational risk) to eliminate systematic product and process defects. Written Order (SfO) Ownership: Maintain, update, and own CMP’s Written Orders, procedures, and work instructions for structural compliance, process consistency, and cross-market operational alignment. Control Function & Stakeholder Interface: Serve as the primary operational contact for 2LoD (Compliance, Risk Management), 3LoD (Internal Audit), and external regulatory stakeholders. Team Leadership & Performance: Direct and mentor Associate/Specialist team members in the matrix structure and cross-functional alignment with Product, Tech (PTX), Legal, and CS. What You Will Bring Minimal requirements:

POSITION SUMMARY: The Service Engineer is an intermediate role focused on troubleshooting, repair, and maintenance of laboratory instrumentation and robotics (such as liquid handlers and analytical instruments). This engineer has more independence than a service engineer 1 and is expected to have a good troubleshooting foundation and understanding of most instruments used in the lab, and can address service events of medium complexity independently and of high complexity with some guidance. The shift timings for this position are Tues - SAT 2:30-11pm. PRIMARY RESPONSIBILITIES: ● Semi-autonomous role. ● Handles more complex troubleshooting, repairs, and maintenance. ● Solves non-routine problems with some guidance. ● Follows SOPs and performs task-based assignments. ● Drafts SOPs and work instructions. Contributes to troubleshooting Wiki. ● Expected to troubleshoot issues of medium to high complexity. Understands when to reach out for guidance. ● Understands "3 pillars" of troubleshooting laboratory automation and show progress in implementation of the pillars. ● Learning to analyze and interpret test data for the purpose of troubleshooting. ● Document service tickets completely and with appropriate detail. Adhere to Good Documentation Practices (GDP). ● Adhere to lab safety protocols and regulatory requirements. QUALIFICATIONS: ● Bachelor’s degree in Engineering, Life Sciences or related field. ● 2–5 years of experience in Service Engineering, with hands-on experience in laboratory equipment repair. ● Understanding of diagnostic laboratory workflows, instrumentation and software. ● Strong knowledge of GDP and regulatory requirements. ● Excellent organizational and communication skills for managing multiple projects KNOWLEDGE, SKILLS, AND ABILITIES: ● Strong mechanical and electrical engineering skills ● Possesses technical expertise and can talk the lingo with customers ● Good listening skills - good customer service skills ● Excellent problem solving skills ● Works

POSITION SUMMARY: Join Natera’s Oncology Research Use Only (RUO) team as a Supervisor for the Signatera Plasma Team. You will direct laboratory staff executing cell-free DNA (cfDNA) extraction, library preparation, and Next-Generation Sequencing (NGS) workflows to advance our personalized Minimal Residual Disease (MRD) assays. Every sample represents a real person, and you will ensure that all lab processes operate with the pace and precision required to support our clinical pipeline. PRIMARY RESPONSIBILITIES: Oversee the daily scheduling of employees executing DNA extractions, library preparation, Nucleic Acid Quality Control (QC), and NGS workflows Conduct regular 1:1 meetings to deliver unvarnished, data-backed performance evaluations and guide career development Take ownership of daily lab operations by directly executing sample processing alongside the team to maintain throughput Serve as the primary technical point of contact, using data to guide team members on data interpretation, next steps, and troubleshooting Execute process development and method/instrument testing to increase operational precision and scale Use data to identify lab process deviations, root-cause the underlying issues, and document findings via nonconformance reports to drive corrective action Draft, generate, and rigorously review Standard Operating Procedures (SOPs) and work instructions Maintain precise records of lab work using Google Sheets, Microsoft Excel, and internal Laboratory Information Management Systems (LIMS) Ensure accurate, ethical, and appropriate management of samples in strict compliance with all applicable federal regulations Think team by partnering directly with Oncology RUO peer groups to eliminate bottlenecks and optimize sample processing without needing translation layers Present data-backed summaries on team activities, project milestones, and timeline adherence Adapt to evolving science and operational needs, taking ownership of tasks that move th

POSITION SUMMARY: The Product Development Sr. Research Associate will contribute to the design, execution and participation in experiments/tasks to support oncology product development and verification and validation (V&V) studies under design control, for next generation sequencing (NGS) assays. We are looking for a meticulous and dedicated candidate with direct laboratory experience in assay development who can work effectively in a fast-paced environment to ensure the highest quality clinical assays are developed and launched for our patients. The ideal candidate will be an enthusiastic and driven professional who is eager to learn, flexible, enjoys multi-tasking and possesses strong wet lab skills. PRIMARY RESPONSIBILITIES : With some supervision, design and execute low to moderate complexity experimental workflows, including cfDNA extraction, library preparation for next-generation sequencing (NGS) using both manual and automated platforms, employing various molecular biology and standard laboratory methods in accordance with standard operating procedures (SOPs) and work instructions Assist with the design, plan and execution of experiments to support the development and V&V of oncology assays Maintain a detailed and organized electronic laboratory notebooks and accurate records of lab work using a variety of software including Google Sheets, Microsoft Excel, and internal databases Analyze and interpret experimental data using appropriate statistical and analytical tools Assist in drafting documentation including study protocols, reports, SOPs and work instructions Coordinate across multiple internal teams to ensure the timely execution of the studies. Adapt to handle multiple tasks and priorities, and perform other duties as assigned Learn the science behind ongoing research projects while actively completing increasingly complex tasks QUALIFICATIONS : Bachelor’s degree in molecular biology, genetics, biochemistry or related field with a minimum

The Team + The Role Pendo is hiring a Senior Account Executive for our Commercial Sales team in Munich, Germany to drive new business across our the DACH region to target prospect accounts. This role is built for high-performing Senior Commercial with a proven track record of closing self generated deals across and running sales motions with autonomy and excellence. You’ll lead complex, multi-stakeholder sales cycles, selling cutting-edge Data & Analytics solutions powered by AI—backed by exciting product innovation and momentum at Pendo—while accelerating growth in one of our most strategic segments. This role is a hybrid position working 3 days per week from our office in Munich. What this looks like day-to-day Win new enterprise logos across Germany and the DACH region Lead complex, multi-stakeholder sales cycles from first engagement to close Consistently deliver and hit quotas Build trusted relationships with C-level and senior decision-makers Develop and execute clear, strategic account plans Position Pendo’s AI-powered Data & Analytics platform as a critical driver of digital transformation Collaborate cross-functionally to win and expand strategic accounts Maintain accurate forecasting and disciplined pipeline management Who You Are You're a builder, not a maintainer. This paragraph does not change: You’re most energized when there isn’t a clear path yet, and you get to define it. You don’t wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great recruiters don’t just follow instructions; they operate as strategic advisors, influencing hiring decisions, guiding stakeholders, and elevating how we attract talent. You're AI-curious - genuinely. This paragraph does not change: You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything; how you source, how you prep for

POSITION SUMMARY The Clinical Lab Supervisor is a leader in Natera’s lab operations whose role is to oversee employees' performance and serve as a liaison between employees and senior management to meet company goals and quality objectives. The supervisor is responsible for daily supervision of lab staff performing duties such as laboratory testing and data review. Duties include but are not limited to coaching, motivating, staffing, evaluating, and training staff. The supervisor works closely with the manager to ensure company and team goals are met while adhering to good manufacturing practices and CLIA/CAP guidelines. The shift timings are from Monday- Friday , 1.00 PM- 9.30 PM PRIMARY RESPONSIBILITIES Responsible for day-to-day staffing/scheduling/setting up sample run schedules. Ensures production work is consistently completed according to department goals. Ensures all case samples are processed and accounted for. Monitors team members to ensure adherence to SOPs and safety procedures Oversees training for new hires: works in conjunction with lead to train new hires. Document nonconformance reports and all corrective actions taken when test systems deviate from the established performance specifications as needed. Escalates protocol deviation to lead/supervisor. Assists manager in initiating and completing CAPAs. Handles employee issues. Collaborates with Manager and/or Human Resources to resolve issues. Ensures alignment with team for reasoning behind instructions/processes and changes Meets regularly with individual team members to discuss goals and progress. Responsible for staff performance reviews. Plans and leads shift meetings Maintains team morale and professionalism of team members, including by acting as role model. Adheres to Departmental Expectations Ensures compliance with all regulatory agency requirements through documentation, audits, and corrective action. Go-to person when manager is not present. May assist lab team in day to day

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you will: Design and run experiments that improve agentic model behavior for complex so

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments th

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people.

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Create ambitious RL environments to push our models to their limits, and measure frontie

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

About the Team The Personal AGI team seeks to empower all of humanity to benefit from frontier intelligence in whatever way they choose. We are responsible for training models to deploy to millions of users globally via ChatGPT, the API, and future products. We aim to evolve ChatGPT from a chatbot to an infinitely capable and personalized superassistant supporting human flourishing. We work on defining, measuring, and improving capabilities across the training stack. Our focus areas include but are not limited to model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, world interaction, and bringing agents to everyone. We chart the course for what to strive towards. We partner closely with research and product teams across the company ensuring that our models are safe, efficient, and reliable. About the Role You’ll work as a Research Engineer / Scientist on the North Stars team within the broader Personal AGI research org. You will work on bringing the next generation of AI-enabled experiences to all of humanity by closing the capability overhang between power users and the average consumer, including areas like tool-use, feature discovery, connectors, and instruction following. You will think deeply about the current bottlenecks in model behavior, translate these insights into robust evals, training data, reward signals, and model and harness improvements. We're looking for individuals with strong ML engineering skills and research experience passionate about creative, product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modelin

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, meas