{"id":2784248,"url":"https://alion.io/job/ss-supply-chain-solutions-principal-data-scientist","title":"Principal Data Scientist","company":{"id":3810750,"name":"SS Supply Chain Solutions","domain":"3scsolution.com","url":"https://alion.io/company/ss-supply-chain-solutions","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","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":{"min":7000000,"max":7500000,"currency":"INR","period":"year","gross":null,"usd_annual":79245},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Docker","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"FastAPI","optional":true},{"name":"Flask","optional":true},{"name":"Function Calling","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"MLFlow","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-05-11T06:10:17Z","employer_posted_date":"2026-05-11","last_verified_at":"2026-10-25T06:08:56Z","board_verified":true,"closed_at":null,"days_open":167,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":166},"description":"About the Role\nWe are looking for a Lead/Principal Data Scientist - Forecasting & Decision Science with 7+ years of experience in building scalable, business-impacting data science solutions across predictive analytics, time series forecasting, machine learning, and applied AI.\nThis role is ideal for someone who is strong in Python, forecasting, advanced analytics, and enterprise-grade model development, and can translate complex business problems into practical, production-ready solutions. The candidate should be comfortable working across the full lifecycle of a data science solution - from problem framing and exploratory analysis to model development, deployment support, business validation, and continuous improvement.\nA strong background in forecasting and predictive analytics is essential. Exposure to supply chain / operations use cases, decision science, or agentic AI systems will be an added advantage.\nWhat You’ll Do\nBuild and deliver predictive analytics and forecasting solutions for business-critical use cases \nDevelop robust models for: Demand Forecasting \nSales Forecasting \nInventory Analytics \nSupply / Operations Planning \nBusiness Performance Forecasting \n\nWork extensively with time series and sequential data, including trend / seasonality modeling, lag and rolling features, forecast validation, backtesting, and performance improvement \nDesign and implement machine learning models for structured and semi-structured business data \nPerform exploratory data analysis, feature engineering, model evaluation, and hypothesis-driven analysis\nTranslate business problems into analytical frameworks, model approaches, features / assumptions, and success metrics \nBuild clean, modular, production-friendly Python solutions\nWork closely with business, product, engineering, and data teams to ensure solutions are practical, scalable, and business-aligned \nSupport deployment and integration of models into enterprise applications / APIs \nMentor junior team members and contribute to solution reviews, model quality, and best practices \nMust Have\n7+ years of relevant experience in Data Science, Machine Learning, Predictive Analytics, or Applied AI \nStrong proficiency in Python for data analysis, model development, and solution engineering \nStrong hands-on experience in: Predictive Analytics\nTime Series Forecasting / Time Series Modeling\nMachine Learning model development\nStatistical analysis and feature engineering\nRegression / classification / forecasting use cases\n\nStrong understanding of time series and sequential data, including: Trend / seasonality analysis \nLag features / rolling features \nForecast validation \nBacktesting \nForecast error analysis and performance tuning \n\nStrong hands-on experience in time series forecasting, predictive analytics, and machine learning, with proficiency in relevant Python-based libraries, frameworks, and model development workflows\nStrong understanding of core data science concepts such as: Supervised / unsupervised learning \nModel validation and error analysis \nFeature selection / importance \nBias-variance trade-offs \nExperimentation and hypothesis-driven analysis \n\nGood understanding of SQL and working with large, structured datasets \nExperience building clean, modular, and production-friendly code\nStrong problem-solving and analytical thinking skills \nAbility to independently convert business problems into: Analytical frameworks \nModel approaches \nFeatures / assumptions \nMetrics and success criteria \n\nStrong stakeholder management and business communication skills, with the ability to work closely with business, product, and engineering teams to understand requirements, align on solution approach, and clearly communicate model outputs, assumptions, and recommendations \nAbility to manage ambiguity, drive discussions with cross-functional stakeholders, and translate business asks into structured analytical solutions \nBasic understanding of: Docker / containers\nPackaging and deployment of Python services / models \nLinux / command-line basics \nAPI integration concepts \n\nAbility to mentor junior data scientists and review their approach / outputs \nGood to Have\nExperience in supply chain / operations domain, especially in one or more of: Demand Forecasting \nInventory Analytics \nSupply Planning \nProduction / Operations Analytics \nLogistics / Distribution Analytics \n\nExposure to optimization / decision-support systems (not mandatory, but beneficial) \nFamiliarity with: FastAPI / Flask\nGit / version control\nMLflow / experiment tracking\nAirflow / workflow orchestration\n\nExposure to cloud environments such as AWS / Azure / GCP\nUnderstanding of MLOps concepts such as: Model packaging \nDeployment workflows \nMonitoring / retraining pipelines \n\nExposure to LLMs / Generative AI / Agentic Systems, including concepts such as: Prompt engineering \nRAG / context-aware AI systems \nTool calling / orchestration \nMulti-agent workflows \n\nAI-assisted analytics / decision support \nExperience working on enterprise-scale analytics or decision intelligence platforms","description_format":"text","description_chars":5058,"description_truncated":false,"requirements":{"experience_years_min":7,"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":["Supply Chain","Supply Chain & Logistics Software"],"lifecycle":[{"event":"open","at":"2026-10-17T13:48:06Z"}],"visa":[],"liveness":{"score":9,"band":"cold","label":"Long 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