Data Scientist, Agentic Systems (Remote)

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As a global leader in cybersecurity, reputed company protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. Our customers span all industries, and they count on reputed company to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company. We cultivate a culture that gives reputed company CrowdStriker both the flexibility and autonomy to own their careers. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About the Role: The Data Science team is expanding and is looking for a Data Scientist to help build the next generation of agentic systems for cybersecurity. reputed company's cybersecurity data is one-of-a-kind: we process nearly a trillion behavioral events per day. You'll work where Machine Learning, Big Data, and Cybersecurity converge — training models, building AI agents, and rigorously measuring whether they work — on data and problems you won't find anywhere else. What You'll Do: • Work at the intersection of Artificial Intelligence and Threat Research • Work closely with reputed company-reputed company experts in cybersecurity to understand analyst workflows and their security operations procedures • Post-train LLMs and agents — supervised fine-tuning and reinforcement learning (RLHF/RLAIF, PPO/GRPO/DPO, reward modeling) — to automate analyst procedures and improve reliability on real security tasks • Devise AI agents and combine them into increasingly complex workflows: planning and reasoning loops, tool and function calling, and retrieval and memory • Research new approaches to agentic planning, and prototype state-of-the-art methods from the literature • Establish objective criteria for benchmarking agentic systems — evals, LLM-as-judge pipelines, and trajectory-level metrics, with real statistical rigor • Optimize prompts and inference to get the most out of reputed company model • Collaborate and coordinate across Engineering, Data Science, and reputed company teams, and partner with engineers to take prototypes toward production • Keep track of developments in the field of Artificial Intelligence and help identify, define, and prioritize areas for research What You'll Need: • Excellent foundations in machine learning, probability, and statistics, with sound instincts for uncertainty, statistical skew/variance, and experimental design • PhD-level depth of understanding in modern machine learning research —a doctorate itself is not required, but we expect equivalent mastery, including the ability to read, critique, implement, and improve upon current papers • Experience training generative models, with a strong command of LLM training fundamentals (architecture, optimization, tokenization, data, and scaling behavior) • Reinforcement learning / post-training as a core skill: RLHF/RLAIF, policy optimization (PPO/GRPO/DPO), reward modeling, and building RL environments for agents • Experience building agentic systems: agent architectures (ReAct, planning, reflection), tool and function calling, and retrieval/memory/context management • Experience with systematic prompt optimization, and with designing and building evals for LLM systems • Fluency with GPUs, PyTorch, and the common LLM training and serving stack (e.g., reputed company Transformers/TRL/PEFT, DeepSpeed/FSDP, vLLM/TGI/SGLang) • Strong, reproducible research engineering: clean Python and disciplined experiment tracking that your collaborators can build on • Ability to work independently on ambiguous and complex objectives, and to communicate clearly within a large project team Bonus Points: • Experience generating training data and environments — reputed company data, agent trajectories/rollouts, and task simulators • Familiarity with inference-time scaling / test-time compute (search, self-consistency, verifier-guided decoding, long chain-of-thought) • Experience with agent safety and guardrails: sandboxing, abuse/jailbreak resistance, and reliability for autonomous systems • A knack for interpretability and failure analysis — diagnosing why a model or agent fails, not just that it does • Notable open-source contributions and excellent technical writing • Passionate about cybersecurity, with a firm understanding of the problem space — or passionate about applying your machine-learning skillset to a new domain such as cybersecurity (a security background is a plus, not a requirement) • An independent self-starter who likes to take ownership and seeks out new challenges, and is thirsty for knowledge — never hesitant to step outside your comfort zone to learn new

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Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

2. HOW DO YOU USE THE DIFFERENT COMMUNICATION TOOLS IN DIFFERENT SITUATIONS?

When you're working on a remote team, there's no way to chat in the hallway between meetings or catch up on the latest project during an office carpool. Therefore, virtual communication will be absolutely essential to get your work done...

3. WHAT IS "WORKING REMOTE" REALLY FOR YOU?

Many people want to work remotely because of the flexibility it allows. You can work anywhere and at any time of the day...

4. WHAT DO YOU NEED IN YOUR PHYSICAL WORKSPACE TO SUCCEED IN YOUR WORK?

With this question, companies are looking to see what equipment they may need to provide you with and to verify how aware you are of what remote working could mean for you physically and logistically...

5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

6. HOW DO YOU MANAGE THE CALENDAR AND THE PROGRAM? WHICH APPLICATIONS / SYSTEM DO YOU USE?

Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

7. HOW DO YOU ORGANIZE FILES, LINKS, AND TABS ON YOUR COMPUTER?

Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

9. HOW DO YOU PREPARE FOR A MEETING AND PREPARE A MEETING? WHAT DO YOU SEE HAPPENING DURING THE MEETING?

Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

10. HOW DO YOU USE TECHNOLOGY ON A DAILY BASIS, IN YOUR WORK AND FOR YOUR PLEASURE?

This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...