{"id":2859846,"url":"https://alion.io/job/weekday-data-scientist-7","title":"Data Scientist","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":88,"ghost_share":0,"stale_share":0.977,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":57000,"period":"year","method":"role_country_seniority_unknown","sample_n":166},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Contrastive Learning","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Hugging Face","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Neo4j","optional":false},{"name":"NLP","optional":false},{"name":"ONNX","optional":false},{"name":"PEFT","optional":false},{"name":"pgvector","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"QLoRA","optional":false},{"name":"Reranking","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"Sentence-Transformers","optional":false},{"name":"SQL","optional":false},{"name":"Transformers","optional":false},{"name":"vLLM","optional":false},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-10-19T15:54:56Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-22T10:42:26Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"'\n: - ( - )\nExperience: 1+ yrs\nLocation: Bangalore\nWe are looking for a talented and technically strong Data Scientist I / II to develop and deploy production-grade machine learning, Natural Language Processing (NLP), and Large Language Model (LLM) solutions. The role focuses on building intelligent systems for entity extraction, classification, semantic retrieval, ranking, and knowledge graph applications using large-scale enterprise datasets.\nThe ideal candidate will have hands-on experience with Python, transformer models, applied NLP, and machine learning, along with a strong understanding of model evaluation and production deployment. This is an opportunity to work on complex AI challenges involving millions of records while building scalable solutions that deliver measurable business value.\nRequirements\nKey Responsibilities\nFine-tune transformer models and LLMs using techniques such as LoRA and QLoRA for entity extraction, classification, and reranking.\nDevelop NLP models to extract, classify, and link entities from resumes, job descriptions, and other unstructured enterprise data.\nBuild prediction models, knowledge graphs, and graph traversal solutions to represent relationships between skills, roles, and competencies.\nDesign and implement semantic retrieval, clustering, and learning-to-rank pipelines across large taxonomies and datasets.\nDevelop embedding-based search solutions using bi-encoders, cross-encoders, and related retrieval techniques.\nApply classical machine learning methods, including gradient boosting, logistic regression, clustering, and dimensionality reduction.\nDesign evaluation frameworks, select appropriate metrics, analyse model errors, and validate performance through systematic experiments.\nExplore datasets containing millions of records using Python, SQL, and data-processing tools.\nDeploy, monitor, and improve machine learning models in production environments.\nUse experiment tracking, model versioning, Docker, and cloud infrastructure to support reproducible ML workflows.\nCollaborate with product, data, and engineering teams to translate business problems into effective AI solutions.\nDocument experiments, communicate findings, and continuously improve model accuracy, efficiency, and reliability.\nWhat Makes You a Great Fit\n1+ years of relevant experience in applied machine learning, NLP, or data science; experience expectations may vary between Data Scientist I and II.\nStrong proficiency in Python, with hands-on experience using PyTorch, Hugging Face Transformers, sentence-transformers, pandas, and scikit-learn.\nPractical experience fine-tuning transformer models on custom datasets for named entity recognition, classification, or related NLP tasks.\nExperience with LLM fine-tuning and parameter-efficient techniques such as PEFT, LoRA, or QLoRA.\nStrong understanding of embeddings, attention mechanisms, contrastive learning, semantic search, and information retrieval.\nWorking knowledge of classical machine learning algorithms and statistical evaluation methods.\nExperience with SQL and the ability to analyse large-scale datasets.\nUnderstanding of model evaluation, sampling, statistical significance, calibration, and metric selection.\nFamiliarity with ML deployment practices, experiment tracking, model versioning, Docker, and GPU-based training or serving on AWS.\nExperience with learning-to-rank, knowledge graphs, entity linking, or large-scale taxonomies is an advantage.\nFamiliarity with Neo4j, Cypher, pgvector, graph ML, GLiNER, NuNER, vLLM, ONNX, AWS Bedrock, or SageMaker is a plus.\nStrong analytical thinking, problem-solving, and written communication skills.\nAbility to work collaboratively, take ownership of experiments, and translate research into production-ready solutions.\nA strong interest in applied AI, modern NLP, LLM systems, and continuous experimentation.","description_format":"text","description_chars":3864,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-19T15:54:56Z"}],"visa":[],"liveness":{"score":31,"band":"fade","label":"Fading","p_open":1,"p_active":0.343,"p_room":0.9,"age_days":2,"expected_fill_days":6,"reasons":["conf:3","agency","stale_co","velocity","win:mid","comp:brand"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/weekday-data-scientist-7","json_url":"https://alion.io/job/weekday-data-scientist-7.json","meta":{"generated_at":"2026-10-22T16:40:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":17150,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":7097},"rest":"https://alion.io/mcp/rest/get_company?id=7097"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fweekday-data-scientist-7"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fweekday-data-scientist-7"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fweekday-data-scientist-7"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/weekday-data-scientist-7\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fweekday-data-scientist-7"}]}