{"id":1360452,"url":"https://alion.io/job/pearson-advanced-specialist-ai-scientist","title":"Advanced Specialist, AI Scientist","company":{"id":34029,"name":"Pearson","domain":"pearson.com","url":"https://alion.io/company/pearson","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":77,"open_postings":22,"ghost_share":0,"stale_share":0.909,"repost_share":0,"time_to_fill_p50_days":26,"computed_at":"2026-10-22T06:10:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"Git","optional":true},{"name":"Hugging Face","optional":true},{"name":"Kubernetes","optional":true},{"name":"Linux","optional":true},{"name":"NLTK","optional":true},{"name":"NumPy","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Snowflake","optional":true},{"name":"spaCy","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true},{"name":"Unix","optional":true}],"status":"live","first_seen_at":"2026-03-09T08:07:37Z","employer_posted_date":"2026-03-09","last_verified_at":"2026-10-22T03:57:58Z","board_verified":true,"closed_at":null,"days_open":227,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":226},"description":"ROLE: Senior AI Scientist\nRole aim\nAre you passionate about AI and Education? We are thrilled to announce a great opportunity to join our international AI organization inside the English Language Learning division as a Senior AI scientist for one of the most critical products in the company. You will workprototyping and implementing artificial intelligence systems for the education sector .\nIn Pearson English Language Learning we aspire to become the world's leading destination to learn, assess and improve English language skills. Our main focus is to deliver our promise to committed learners from around the world, who want to reach their full potential through learning English.\nRole profile\nThis position requires an experienced and fully competent professional with a broad set of skills in data engineering, statistical reasoning and modelling for educational measurement, applied machine learning research, and possibly also basic leadership skills.\nThis role requires minimal guidance. It can be considered to be an entry-level manager role, which may supervise and/or lead colleagues with less experience.\nEstimated time spent on various task types:\nNew features: 50-70% \nDocumentation: 15% \nMeetings, incl. supervision: 10-30% \nMaintenance: 5% \nResponsibilities\nDepending on current needs, the role may be responsible for: \nLeading significant parts of work in the lifecycle of development of learning educational capabilities \nResearch & development in the field of creating data-driven educational products and solutions \nDesigning, implementing and maintaining learning capabilities based on machine-learning and statistics, in collaboration with Engineering teams \nDesigning frameworks for monitoring capabilities performance on production (in collaboration with Engineering teams); evaluating results for improvement \nCreating and conducting internal trainings \nCreating technical documentation, incl. patent documentation \nSharing work results internally and externally (publications, conferences, meetups) \nStaying up to date with state-of-the-art methods in the scope of own specialisation, e.g. NLP, speech processing, statistical modelling, psychometrics \nProviding input into team vision, goals, and processes \nLeading, mentoring and coaching a small group of direct reports (from intern to regular level data scientists) \nSupervising or leading colleagues with less experience \nMost desirable qualifications:\nExperience with generative AI models and techniques. \nStrong collaboration with engineering teams to develop and implement AI solutions. \nProven experience in building production-ready machine learning models to solve diverse set of business problems. \nGood knowledge of statistical modelling and machine learning theory \nStrong proficiency in Python and machine learning frameworks, e.g. pandas, numpy, scikit-learn, NLTK, spaCy, Hugging Face, TensorFlow, PyTorch \nStrong hands-on experience in using state-of-the-art methods in the scope of own specialisation, e.g. NLP, speech processing, statistical modelling, psychometrics, reinforcement learning \nProficiency in SQL and relational databases \nAbility to translate business needs into research problems \nAbility to apply best practices for machine learning and software engineering \nExperience with Git-based code review \nProficiency in Linux, Unix or macOS \nSome experience in working with non-technical stakeholder \nAt least intermediate presentation and mentoring skills \nAbility to work in a diverse, remote, asynchronous team \nCollaboration skills, e.g. being able to give (and receive) feedback \nProficiency in written and spoken English and a key local language \nNice to have:\nFamiliarity / experience with: \nMLOps and DevOps \nDocker and Kubernetes \ncloud infrastructure, preferably AWS, Azure \ncloud data processing, e.g. Snowflake or AWS Redshift \ndistributed data processing, e.g. Spark \nLocation:\nWe are looking for an individual in Spain or Poland 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