{"id":3079392,"url":"https://alion.io/job/forbes-data-scientist","title":"Data Scientist","company":{"id":8272,"name":"Forbes","domain":"forbes.com","url":"https://alion.io/company/forbes-advisor","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":85,"open_postings":12,"ghost_share":0.167,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":68,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":15000,"max_usd":37000,"period":"year","method":"role_seniority_country_cell","sample_n":26},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Time Series","optional":false},{"name":"Embeddings","optional":true},{"name":"GCP","optional":true},{"name":"Google BigQuery","optional":true},{"name":"NLP","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-10-22T11:35:15Z","employer_posted_date":null,"last_verified_at":"2026-10-22T11:35:15Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"We're hiring a Data Scientist to help us unlock growth through advanced analytics and machine learning. This role sits at the intersection of marketing performance, product optimization, and decision science. You'll partner closely with paid media, product, and engineering to build models, generate insights, and influence how we acquire, retain, and monetize users. From campaign ROI to user segmentation and funnel optimization, your work will directly shape how we grow. This role is ideal for someone who thrives on business impact, communicates clearly, and wants to build reusable, production-ready insights, not just run one-off analyses.\n\nThe core responsibilities for the job include the following:\n\nMarketing and Revenue Modelling: \nOwn end-to-end modelling of LTV, user segmentation, retention, and marketing efficiency to inform media optimization and value attribution.\nCollaborate with paid media and revOps to optimize SEM performance, predict high-value cohorts, and power strategic bidding and targeting.\n\nProduct and Growth Analytics: \nWork closely with Product Insights and General Managers (GMs) to define core metrics, KPIs, and success frameworks for new launches and features.\nConduct deep-dive analysis of user behavior, funnel performance, and product engagement to uncover actionable insights.\nMonitor and explain changes in key product metrics, identifying root causes and business impact.\nWork closely with data engineering to design and maintain scalable data pipelines that support machine learning workflows, model retraining, and real-time inference.\n\nPredictive Modelling and Machine Learning: \nBuild predictive models for conversion, churn, revenue, and engagement using regression, classification, or time-series approaches.\nIdentify opportunities for prescriptive analytics and automation in key product and marketing workflows.\nSupport development of reusable ML pipelines for production-scale use cases in product recommendation, lead scoring, and SEM planning.\n\nCollaboration and Communication: \nPresent insights and recommendations to a variety of stakeholders from ICs to executives clearly and compellingly.\nTranslate business needs into data problems and complex findings into strategic action plans.\nWork cross-functionally with Engineering, Product, BI, and Marketing to deliver and deploy your work.\n\nRequirements: \nBachelor's degree in a quantitative field (mathematics, statistics, CS, engineering, etc. ).\n5+ years in data science, growth analytics, or decision science roles.\nStrong SQL and Python skills (Pandas, Scikit-learn, NumPy).\nHands-on experience with Tableau, Looker, or similar BI tools.\nFamiliarity with LTV modelling, retention curves, cohort analysis, and media attribution.\nExperience with GA4 Google Ads, Meta, or other performance marketing platforms.\nClear communication skills and a track record of turning data into decisions.\n\nNice to Have: \nExperience with BigQuery and Google Cloud Platform (or equivalent).\nFamiliarity with affiliate or lead-gen business models.\nExposure to NLP, LLMs, embeddings, or agent-based analytics.\nAbility to contribute to model deployment workflows (e. g., using Vertex AI, Airflow, or Composer).\nSkills\npython, scikit-learn, sklearn, 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