{"id":3701385,"url":"https://alion.io/job/weekday-data-scientist-9","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":93,"ghost_share":0,"stale_share":0.978,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-05T05:54:30Z"}},"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":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"dbt","optional":false},{"name":"GCP","optional":false},{"name":"Julia","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-11-03T19:36:24Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-05T11:26:21Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"'\n: - ( - )\nExperience: 8+ yrs\nLocation: Bangalore\nAs a Data Scientist, you will lead the development of sophisticated price elasticity models that drive strategic pricing decisions across diverse product lines. Leveraging advanced econometric techniques and machine learning algorithms, you will analyze large-scale transactional data, consumer behavior patterns, and market dynamics to quantify price sensitivities and forecast demand shifts. Your insights will directly influence pricing strategies, promotional planning, and revenue optimization initiatives, ensuring that business objectives are met with data-driven precision. In a fast-paced, collaborative environment, you will partner with cross-functional teams to translate analytical findings into actionable business recommendations.\nRequirements\nDesign, implement, and validate nonlinear and parametric price elasticity models using econometric and machine learning methods.\nExtract, clean, and preprocess large volumes of sales, pricing, and consumer data from multiple sources.\nConduct hypothesis testing, causal inference, and scenario analysis to evaluate pricing experiments and promotional campaigns.\nDeploy predictive models into production pipelines, ensuring scalability and robustness for real-time pricing decisions.\nCreate interactive dashboards and visualizations to communicate model insights to stakeholders.\nCollaborate with product, marketing, and finance teams to align modeling efforts with business strategy.\nStay abreast of industry trends, emerging techniques, and best practices in price optimization.\nDocument modeling workflows, assumptions, and results for audit and reproducibility.\nMentor junior analysts and provide technical guidance on data science methodologies.\nContinuously monitor model performance, conduct post-deployment reviews, and iterate improvements.\n8+ years of experience in data science with a strong focus on pricing and demand modeling.\nProficiency in statistical programming languages such as Python, R, or Julia, and familiarity with SQL and data warehousing concepts.\nDeep knowledge of econometric techniques (e.g., logit, probit, BLP) and machine learning models (e.g., random forest, XGBoost) applied to price elasticity.\nDemonstrated ability to build end-to-end analytical solutions from data ingestion to model deployment.\nStrong analytical mindset with a proven track record of turning complex data into actionable business insights.\nExcellent communication skills for presenting technical findings to non-technical audiences.\nExperience working in a dynamic, cross-functional team environment.\nFamiliarity with cloud platforms (AWS, GCP, Azure) and data pipeline tools (Airflow, dbt).\nAbility to navigate ambiguous problems, iterate rapidly, and deliver high-impact solutions.\nPassion for continuous learning and staying current with the latest research in pricing analytics.","description_format":"text","description_chars":2896,"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":["Continuous 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