{"id":2802535,"url":"https://alion.io/job/minds-print-data-scientist-supply-chain-inventory-analytics","title":"Data Scientist - Supply Chain & Inventory Analytics","company":{"id":3223551,"name":"Minds Print","domain":"mindsprint.com","url":"https://alion.io/company/mindsprint-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Darwinbox","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14000,"max_usd":36000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":21},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Prophet","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Statsmodels","optional":false},{"name":"Time Series","optional":false},{"name":"XGBoost","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"MLFlow","optional":true},{"name":"Plotly","optional":true},{"name":"Power BI","optional":true},{"name":"Streamlit","optional":true}],"status":"live","first_seen_at":"2026-08-10T05:06:15Z","employer_posted_date":null,"last_verified_at":"2026-08-10T05:06:15Z","board_verified":false,"closed_at":null,"days_open":73,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":73},"description":"Data Scientist - Supply Chain & Inventory Analytics\n\nExperience : 4 to 6 years\n\nLocation : Chennai\n\nNote : We are looking for candidates who are currently serving notice or candidates who can join us immediately.\n\nKey Responsibilities : \n\n- Translate ambiguous operational problems stated by planners and engineers, not by data teams, into well-posed modelling problems with clear success measures.\n\n- Build, validate, and productionise forecasting, optimisation, and regression models on real enterprise data (SAP MM / PM extracts, consumption history, purchase-order history, master data).\n\n- Do the unglamorous data work properly : profiling, reconciliation, deduplication of SKU masters, handling intermittent and lumpy demand, and dealing with sparse or missing history.\n\n- Design fallback and cold-start strategies so that models degrade gracefully rather than producing confident nonsense on thin data.\n\n- Build explainability into every output - a planner must be able to see why a number moved before they will act on it.\n\n- Partner with product, engineering, and design to ship models into a live application, including the schema contracts, validation rules, and retraining behaviour the application depends on.\n\n- Run model monitoring and periodic retraining; investigate drift and degradation against ground truth from the field.\n\n- Present findings and recommendations to senior client stakeholders - plant heads, materials management, and procurement leadership - in operational language, with the assumptions and limitations stated plainly.\n\n- Document methodology to a standard that survives audit, client scrutiny, and your own handover.\n\nRequired Qualifications : \n\n- Experience : 4 to 6 years in a data science, applied machine learning, or quantitative analytics role, with at least two years working on problems that reached production or live business use.\n\n- Education : Bachelor's or Master's in Statistics, Mathematics, Computer Science, Operations Research, Industrial Engineering, Economics, or a related quantitative discipline.\n\n- Programming : Strong Python - pandas, NumPy, scikit-learn, statsmodels. Comfortable writing clean, testable, reviewable code rather than notebook-only exploration.\n\n- SQL : Confident with complex joins, window functions, and query performance on large operational tables.\n\n- Time-series forecasting : Practical experience with classical and modern approaches - ARIMA/SARIMA, exponential smoothing, Prophet, gradient-boosted trees for tabular time series - and the judgement to know when a simple baseline is the right answer.\n\n- Supervised learning : Solid grounding in regression and tree-based ensembles (XGBoost, LightGBM, Random Forest), including feature engineering, regularisation, cross-validation design, and honest error analysis.\n\n- Statistical fluency : Distributions, uncertainty quantification, confidence and prediction intervals, hypothesis testing, and the ability to explain what a model does not know.\n\n- Communication : Able to explain a model to a plant engineer with no statistics background and to defend it to a technically sharp reviewer, in the same week.\n\nPreferred / Good to Have : \n\n- Domain exposure to supply chain, inventory optimisation, spare-parts planning, MRO, maintenance planning, or procurement analytics.\n\n- Familiarity with inventory theory - safety stock formulations, service-level targets, EOQ, reorder point logic, multi-echelon inventory concepts.\n\n- Experience with intermittent and lumpy demand methods (Croston, SBA, TSB) - highly relevant for spare parts, where most SKUs move rarely.\n\n- Optimisation experience : linear/mixed-integer programming with PuLP, OR-Tools, Gurobi, or similar.\n\n- Working knowledge of SAP data structures (MM, PM, MRP) or comparable ERP extracts.\n\n- Exposure to asset-heavy sectors - power generation, oil and gas, mining, heavy manufacturing, utilities, or process industries.\n\n- Condition-monitoring, predictive maintenance, IoT sensor data, or reliability engineering (RCM, FMEA) exposure.\n\n- MLOps practice : MLflow, Docker, CI/CD for models, experiment tracking, model registries.\n\n- Cloud platforms - Azure, AWS, or GCP - and their data and ML services.\n\n- Visualisation and storytelling : Power BI, Plotly, Streamlit, or building analytical front-ends that non-analysts actually use.\n\n- Awareness of data-residency and security expectations in the Indian public-sector and regulated-enterprise context (single-tenant deployments, CERT-In alignment).\nSkills\nData Science, Data Scientist, SAP MM, MLOps, Machine Learning, Artificial Intelligence, SQL, Time Series Forecasting, FSCM","description_format":"text","description_chars":4625,"description_truncated":false,"requirements":{"experience_years_min":4,"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","IT Consulting & Digital Transformation","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-18T01:22:52Z"}],"visa":[],"liveness":{"score":5,"band":"cold","label":"Long shot","p_open":0.4,"p_active":0.473,"p_room":0.28,"age_days":73,"expected_fill_days":25,"reasons":["seen:73","velocity","win:tail","crowd:"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/minds-print-data-scientist-supply-chain-inventory-analytics","json_url":"https://alion.io/job/minds-print-data-scientist-supply-chain-inventory-analytics.json","meta":{"generated_at":"2026-10-22T20:48:52Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":4994,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":3223551},"rest":"https://alion.io/mcp/rest/get_company?id=3223551"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fminds-print-data-scientist-supply-chain-inventory-analytics"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fminds-print-data-scientist-supply-chain-inventory-analytics"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fminds-print-data-scientist-supply-chain-inventory-analytics"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/minds-print-data-scientist-supply-chain-inventory-analytics\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fminds-print-data-scientist-supply-chain-inventory-analytics"}]}