{"id":2654829,"url":"https://alion.io/job/loreal-data-analyst","title":"Data Analyst","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":"B","score":84,"open_postings":40,"ghost_share":0,"stale_share":0.625,"repost_share":0,"time_to_fill_p50_days":23,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Johannesburg, South Africa"],"countries":["ZA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":34000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":9},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"BigQuery","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Looker","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"Power BI","optional":true},{"name":"Python","optional":true},{"name":"SciPy","optional":true},{"name":"SQL","optional":true},{"name":"Tableau","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-10-15T22:41:01Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-16T06:11:22Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Data Analyst\nLocation: SA and SSA\nReporting To: Data Lead\nAbout L'Oréal:\nL'Oréal has devoted itself to beauty for over 100 years. With its unique international portfolio of 36 diverse and complementary brands, the Group generated sales amounting to 41.18 billion euros in 2023 and employs 90,000 people worldwide. As the world’s leading beauty company, L'Oréal is present across all distribution networks: mass market, department stores, pharmacies and drugstores, hair salons, travel retail, branded retail, and e-commerce. Research and innovation, and a dedicated research team of 4,000 people, are at the core of L'Oréal’s strategy, working to meet beauty aspirations all over the world. L'Oréal’s sustainability commitment, “L'Oréal for the Future,” sets ambitious sustainable development objectives across the Group’s value chain.\nJob Summary:\nWe are seeking a highly analytical and detail-oriented Data Analyst to join our dynamic team. The Data Analyst will be responsible for collecting, analyzing, and interpreting large datasets to provide actionable insights that drive business decisions across various functions, including marketing, sales, product development, and operations. This role requires a strong understanding of statistical analysis, data visualization, and reporting tools, coupled with excellent communication skills to present findings to stakeholders at all levels. The ideal candidate will be passionate about uncovering trends, identifying opportunities, and contributing to the continuous improvement of our business strategies.\nKey Responsibilities:\n Data Collection & Preparation:Gather, clean, and validate data from various internal and external sources (e.g., CRM, ERP, web analytics, social media, market research).\nDevelop and maintain robust data pipelines and ensure data integrity and accuracy.\nPerform data transformations and feature engineering to prepare data for analysis.\n\nData Analysis & Modeling:Conduct in-depth statistical analysis, hypothesis testing, and exploratory data analysis to identify trends, patterns, and anomalies.\nDevelop and implement predictive models, segmentation analyses, and A/B testing frameworks to evaluate business initiatives.\nUtilize various analytical techniques to answer complex business questions and forecast future outcomes.\n\n Reporting & Visualization:Design, develop, and maintain interactive dashboards and reports using data visualization tools to present key performance indicators (KPIs) and insights.\nCreate clear, concise, and compelling presentations to communicate analytical findings and recommendations to non-technical audiences.\nAutomate reporting processes to improve efficiency and timeliness of information delivery.\n\n Insight Generation & Recommendation:Translate complex data findings into clear, actionable business recommendations that support strategic decision-making.\nCollaborate with cross-functional teams (e.g., Marketing, Sales, Product, Finance) to understand business needs and deliver relevant insights.\nProactively identify opportunities for data-driven improvements in business processes and performance.\n\nTool & Process Improvement:Stay up-to-date with industry best practices, new tools, and technologies in data analytics.\nContribute to the continuous improvement of data infrastructure, analytical methodologies, and reporting standards.\nDocument analytical processes, data definitions, and reporting methodologies.\n\nQualifications:\nEducation: Bachelor’s degree in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Economics, Business Analytics, or a related discipline. A Master's degree is a plus.\nExperience: 2-5 years of experience in a Data Analyst, Business Intelligence Analyst, or similar role, preferably within a consumer goods, retail, or e-commerce environment.\nSkills & Competencies:\n Technical Skills:Strong SQL proficiency for data extraction, manipulation, and analysis is essential.\nProficiency in data analysis tools and programming languages such as Python (Pandas, NumPy, SciPy) or R.\nExperience with data visualization tools (e.g., Tableau, Power BI, QlikView, Google Data Studio, Looker).\nFamiliarity with data warehousing concepts and cloud platforms (e.g., AWS Redshift, Google BigQuery, Azure Synapse) is a plus.\nKnowledge of statistical modeling techniques (regression, clustering, time series analysis).\nExperience with Google Analytics, Adobe Analytics, or similar web analytics platforms.\n\nAnalytical & Problem-Solving Skills:Exceptional analytical and problem-solving abilities, with a keen eye for detail and accuracy.\nAbility to interpret complex data and translate findings into clear, actionable insights.\nStrong critical thinking skills to identify root causes and develop effective solutions.\n\nCommunication & Interpersonal Skills:Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.\nStrong presentation skills, capable of delivering compelling narratives based on data.\nAbility to collaborate effectively in a team-oriented environment and build strong relationships with cross-functional teams.\n\nOther Attributes:Self-motivated and proactive, with a strong sense of ownership and accountability.\nAbility to manage multiple priorities and projects in a fast-paced, dynamic environment.\nCuriosity and a continuous learning mindset to stay updated with industry trends.\n\nWhat We Offer:\nA stimulating and international working environment within the world's leading beauty company.\nOpportunities for professional growth, continuous learning, and career development.\nExposure to cutting-edge technologies and innovative data science practices.\nCompetitive salary and benefits package.\nA culture that values diversity, inclusion, and entrepreneurship.","description_format":"text","description_chars":5827,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cosmetics & Makeup","Skincare","Hair Care Products"],"lifecycle":[{"event":"open","at":"2026-10-15T22:41:01Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely 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