{"id":1455649,"url":"https://alion.io/job/insurance-insider-data-scientist","title":"Data Scientist","company":{"id":680067,"name":"Insurance Insider","domain":"insuranceinsider.com","url":"https://alion.io/company/insuranceinsider","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sofia, Bulgaria"],"countries":["BG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":82000,"period":"year","method":null,"sample_n":3503},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Claude","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Recommender Systems","optional":true}],"status":"live","first_seen_at":"2026-09-29T09:46:39Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-09-30T17:47:26Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About Insurance Insider\nInsurance Insider is the leading provider of insights and analysis for the world’s top insurers, distributors, service providers, and investors.\nSince 1996, we’ve been helping clients uncover new business opportunities and protect against risks through our exclusive news, deep analysis and actionable insights on the insurance market. Our coverage extends across the London market, global (re)insurance market, insurance-linked securities market and US property and casualty market.\nAbout the Role\nWe'relooking for a Data Scientist with growing data science skills to join our data team.\nMuch of the role is about structuring and formatting data - turning usage data, article content and other inputs into clean, ready-to-use formats that power personalisation, content recommendationsand other product features. Sothe traditional data engineering work of building and maintainingpipelines will form the base, but the skills to derive value from that data are what's key for this role, along with the ability to use AI to do that quickly.\nThis may suit someone with a software or data engineering background who has moved into data science over the past few years and wants to keep developing in that direction - or a generalist who's happy moving between engineering and data science work rather than a deep specialist in either.\nWe'llsoon be bringing in a lot of new data and new data types from external sources, which will make this data structuring and manipulation work even more central to the role.\nWe’relooking for a self-starter, able to work by themselves and not need to be told what to do. Their mindset is as important as their technical skills - they will be comfortable with experimentation and not necessarily following a strict process. They will have a passion to build products which can create business value andwill be working as part of a small data team of 3.\nKey Responsibilities\nData Structuring & Preparation\nTurn raw, messyor unstructured data - article text, usage data, and new data arriving from external sources - into clean, ready-to-use formats for downstream products.\nApply light ML/NLP techniques (e.g., entity extraction, classification, tagging) to structure unstructured text.\nAdapt existing pipelines to ingest and normalise new data types as they come online.\nBring in new datasets - scraped or paid-for/third-party - and merge them with our existing data to create new, value-add content sets.\nPersonalisation & Content Intelligence\nBuild personalisation logic that blends usage data with content suggestions, helping surface the right content to the right customer.\nWork with product and editorial to define the signals and rules behind personalised recommendations and content creation.\nData Science\nUse statistical and ML methods (e.g. classification, clustering, embeddings) to analyse usage and content data, surfacing patterns and insights that inform personalisation and product decisions.\nUse LLMs to extract structure - keywords, entities, and topics - from unstructured article text, andcheck the accuracy and quality of that output.\nPrototype and test simple models or scoring logic (e.g., for recommendations or content matching), working with product to validatethey add value before scaling.\nTry different approaches to a data or personalisation problem, evaluate what works, and explain the trade-offs in plain terms to non-technical stakeholders.\nData Engineering\nMaintain and extend our Databricks/Python pipelines - ingestion, transformation, schedulingand monitoring.\nIdentifynew data sources relevant to the product and help scope their integration.\nAI-Assisted Development & Collaboration\nUse AI coding tools (e.g., GitHub Copilot, Claude, Cursor) to build and iterate on data pipelines and structuring work quickly.\nWork across product, editorial and commercial teams to understand data needs and communicate findings clearly to non-technical audiences.\nMonitor data quality in production, flagging issues and improving tooling and documentation.\nRequired Experience\n3-5 years' hands-on experience in data engineering, with strong Python and SQL.\nExperience building and maintainingdata pipelines, ideally with Databricks, Spark or a comparable cloud data platform.\nSome exposure to - or a strong interest in developing - data science/ML techniques\nExperience turning raw or messy data into structured, ready-to-use formats for downstream use.\nComfortable working independently and using AI coding tools to move quickly.\nPreferred Qualifications\nExperience with personalisation, recommendation systems, or blending usage/behavioural data with content.\nExposure to using LLMs to extract structure (keywords, entities, topics) from unstructured text.\nA degree in Computer Science, Data Science, Engineeringor a related field - or equivalent experience. We care more about the quality of your work than where you studied.\nExperience with orchestration tools such as Airflow, Dagsteror Databricks Workflows.\nThey may have some data analytics experience - querying and storing data, data preparation, data pipelinesand visualisation. \nWhat We Offer\nA role with real scope to shape how the business understands its customers, with room to grow into a broader remit over time\nReal trust and autonomy - we back people who take ownership and run with initiative\nFlexibility with true hybrid working - expectedto be in the office 1 day a week\nCompetitive compensation and benefits package.\n25 holiday days per year, plus your birthday off\nA collaborative and mission-driven culture\nOpportunities for professional growth and development","description_format":"text","description_chars":5615,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Hybrid work"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial News & Media"],"lifecycle":[{"event":"open","at":"2026-09-29T09:46:39Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":38,"reasons":["conf:6","win:early"],"computed_at":"2026-09-30T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/insurance-insider-data-scientist","json_url":"https://alion.io/job/insurance-insider-data-scientist.json","meta":{"generated_at":"2026-10-01T03:36:06Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3109,"day_limit":5000,"remaining_today":1891,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}