{"id":3472785,"url":"https://alion.io/job/loreal-data-scientist","title":"Data Scientist","company":{"id":1047779,"name":"L'Oréal","domain":"loreal.com","url":"https://alion.io/company/loreal-3","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Radancy","truth_index":{"grade":"A","score":92,"open_postings":126,"ghost_share":0,"stale_share":0.333,"repost_share":0.008,"time_to_fill_p50_days":29,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18500,"max_usd":40000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CatBoost","optional":false},{"name":"GCP","optional":false},{"name":"GitHub","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prophet","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-10-29T17:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-29T17:35:00Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"Responsibilities: \nDesign, develop, implement, and maintain data science and machine learning solutions to meet enterprise goals.\nCollaborate with cross-functional teams to leverage statistical modeling, machine learning, and data mining techniques to improve forecast accuracy and aid strategic decision-making across the organization.\nScale the proven AI-ML product across the SAPMENA region.\nDeep understanding of business/functional needs, problem statements, and objectives/success criteria.\nDevelop and maintain sophisticated statistical forecasting models, incorporating factors such as seasonality, promotions, media, traffic, and other economic indicators.\nCollaborate with internal and external stakeholders, including business, data scientists, and the product team, to understand the business and product needs and translate them into actionable data-driven solutions.\nReview MVP implementations, provide recommendations, and ensure data science best practices and guidelines are followed.\nEvaluate and compare the performance of different forecasting models, recommending optimal approaches for various business scenarios.\nAnalyze large and complex datasets to identify patterns, insights, and potential risks and opportunities.\nCommunicate forecasting results and insights to both technical and non-technical audiences through clear visualizations and presentations.\nStay up to date with the latest advancements in forecasting techniques and technologies, continuously seeking opportunities for improvement.\nContribute to the development of a robust data infrastructure for AI-ML solutions, ensuring data quality and accessibility.\nCollaborate with other data scientists and engineers to build and deploy scalable AI-ML solutions.\n\nRequirements: \n5+ years in developing and implementing forecasting models.\nProven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration).\nProven expertise in time series analysis, regression analysis, and other statistical modelling techniques.\nExperience in ML algorithms such as ARIMA, Prophet, Random Forests, and gradient boosting algorithms (XGBoost, LightGBM, and CatBoost).\nExperience in model explainability with Shapley plots and data drift detection metrics.\nStrong programming and analysis skills with Python and SQL, including experience with relevant forecasting packages.\nPrior experience in data science and ML engineering on Google Cloud.\nProficiency in version control systems such as GitHub.\nStrong organizational capabilities and ability to work in a matrix/multidisciplinary team.\nExcellent communication and presentation skills, with the ability to explain complex technical concepts to a non-technical audience.\nExperience in beauty or the retail/FMCG industry is preferred.\nExperience in handling large volumes of data (> 100 GB).\nExperience in delivering AI-ML projects using Agile methodologies is preferred.\nProven ability to work proactively and independently to address product requirements and design optimal solutions.\nSkills\nARIMA, CatBoost, Demand Forecasting, Gradient Boosting, LightGBM, Prophet, Python, Random Forests, SQL, XGBoost","description_format":"text","description_chars":3180,"description_truncated":false,"requirements":{"experience_years_min":5,"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":["Cosmetics & Makeup","Skincare","Hair Care 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