Applied Data Scientist
2 days ago
Alicante
ph3The Company /h3 pGitKraken is the developer experience (DevEx) platform of choice for more than 40 million developers and 100,000 organizations globally. Combining built‑in AI and powerful workflow orchestration, GitKraken empowers development teams to eliminate unnecessary toil, streamline collaboration, and accelerate productivity. GitKraken’s seamless integrations with leading Git providers, issue tracking tools, and AI solutions make it the most versatile DevEx platform available across desktop, command line, IDE, web, and mobile environments. /p h3The Role /h3 pAt GitKraken, our goal is to help developers and their teams focus, create, and collaborate while minimizing distractions, context switching, and wasted time. Our developer experience platform supports millions of developers across desktop, command line, IDE, browser, web, and mobile. /p pWe’re looking for a pragmatic, startup‑minded Senior Machine Learning Engineer or Applied Data Scientist who can take an idea from concept to production. Sometimes that idea will come from the data, sometimes it will come from the business. In both cases, you’ll be expected to determine what’s possible, identify the fastest credible path forward, and ship solutions that create measurable impact. /p pThis is a high‑ownership role for someone comfortable working across data, product, and engineering. You should be able to frame ambiguous problems, explore messy data, build models or heuristics, integrate with production systems, measure outcomes, and iterate quickly. We care about practical impact, traction, and speed of learning. We are not looking for someone who waits for perfect specs or over‑polishes a solution before proving it matters. /p h3What You’ll Do /h3 ul liIdentify high‑value opportunities from product, customer, and operational data /li liEvaluate ambiguous ideas quickly and determine what is feasible, useful, and worth shipping /li liBuild practical 80/20 solutions that create leverage quickly, then refine them based on traction /li liOwn end‑to‑end execution across data exploration, modeling, experimentation, backend integration, and productization /li liPartner with engineering, product, design, and leadership to turn rough ideas into shipped capabilities /li liUse ML, analytics, heuristics, and automation pragmatically rather than forcing a model where one is not needed /li liDefine success metrics, instrument outcomes, and improve solutions based on real‑world usage /li liHelp shape how GitKraken uses AI and data to improve developer workflows, team velocity, and product experience /li /ul h3Our Tech Lens /h3 pWe value strong fundamentals over a rigid checklist and are always open to adopting new technologies. Here is a snapshot of our current ecosystem: /p ul liLanguages: Python (for data/ML execution), Go, and TypeScript across our core product and backend environments. /li liData Infrastructure: Snowflake for data warehousing, AWS for cloud infrastructure, and Datadog for monitoring and observability. /li liAI Ecosystem DevEx: We heavily leverage and build around modern AI development tools and LLMs like Cursor, Claude Code, and Codex to accelerate execution and shape the future of workflows. /li /ul h3What We’re Looking For /h3 ul liDeep experience in machine learning, applied AI, or a similarly hands‑on product data role at a senior level /li liA track record of shipping data or ML‑powered capabilities into real products or operational workflows /li liComfort moving from messy problem statements to practical execution without a lot of structure /li liAbility to work across the stack, not just in notebooks /li liStrong product judgment and a bias toward simple solutions that deliver measurable value /li liExperience deciding whether a problem is best solved with ML, rules, analytics, automation, or workflow design /li liAbility to balance speed and rigor, including knowing when “good enough to learn” is the right answer /li liStrong communication skills and the ability to explain tradeoffs clearly to technical and non‑technical partners /li liOwnership mindset: you don’t wait for perfect specs, and you follow through from idea to impact /li liProficiency in English is required for this role /li /ul h3Bonus Points /h3 ul liYou’ve built and shipped data or ML‑powered features, not just analyses /li liYou can prototype quickly and are comfortable refining after launch /li liYou know how to avoid getting buried in edge cases before the core value is proven /li liYou like working in a company with a bias toward action, accountability, and high ownership /li liYou want your work to directly influence product direction and business outcomes /li /ul h3How You’ll Be Rewarded /h3 ul liCompetitive compensation with annual performance‑based pay increases /li liFlexible paid‑time‑off policy and paid company holidays (chosen by our employees) /li liGenerous paid parental leave /li liPet insurance plan (with no exclusions) /li liHealth, dental, and vision insurance with competitive employer cost‑sharing /li liModern, fully equipped offices designed to maximize productivity in a hybrid environment /li liGreat Place to Work certified culture /li liPaid career development opportunities, audiobook subscriptions, and mentorship /li li401(k) retirement plan with company matching /li liCompany‑paid domestic trip after your 1‑year anniversary and an international trip every 5 years /li /ul /p #J-18808-Ljbffr