{"id":1251908,"url":"https://alion.io/job/digitalcubez-data-scientist","title":"Data Scientist","company":{"id":3800776,"name":"DIgitalcubez","domain":"digitalcube-cs.com","url":"https://alion.io/company/digitalcubez-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","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":17000,"max_usd":48000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":276},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Pandas","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 Forecasting","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-09-16T09:48:27Z","employer_posted_date":null,"last_verified_at":"2026-09-16T09:48:27Z","board_verified":false,"closed_at":null,"days_open":11,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":11},"description":"DATA SCIENTIST - TIME SERIES FORECASTING\n\nAre you a Data Scientist who loves turning historical data into accurate predictions and actionable business insights?\n\nWere looking for a Data Scientist with strong hands-on experience in Time-Series Forecasting, Machine Learning, Python/R and SQL to build forecasting solutions that directly support business growth, demand planning and supply-chain decisions.\n\nKEY RESPONSIBILITIES :\n\n- Build and scale robust time-series forecasting models for demand, sales and supply-chain metrics.\n\n- Clean, process and analyse large volumes of historical data from multiple sources.\n\n- Experiment with statistical and machine-learning algorithms to improve forecasting accuracy.\n\n- Deploy models into production and continuously monitor their performance.\n\n- Collaborate with product and business teams to convert complex data insights into practical business strategies.\n\nMUST-HAVE SKILLS :\n\n- Data Science, Data Forecasting / Time-Series Forecasting\n\n- Python or R, SQL\n\n- ARIMA, Exponential Smoothing, Prophet, XGBoost, LightGBM\n\n- Pandas, Scikit-learn, Statsmodels, MLflow / ML Tracking Tools\n\nGOOD TO HAVE :\n\n- Experience with Deep Learning models such as LSTM/RNN will be an added advantage.\n\nSkills\nMachine Learning, Data Science, Python, SQL, Pandas, Time Series Forecasting, Data Scientist, Artificial Intelligence","description_format":"text","description_chars":1356,"description_truncated":false,"requirements":{"experience_years_min":2,"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":[],"lifecycle":[{"event":"open","at":"2026-09-25T18:04:06Z"}],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.724,"p_room":0.75,"age_days":10,"expected_fill_days":15,"reasons":["seen:10","velocity","win:late","comp:junior"],"computed_at":"2026-09-27T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/digitalcubez-data-scientist","json_url":"https://alion.io/job/digitalcubez-data-scientist.json","meta":{"generated_at":"2026-09-28T01:01:22Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":596,"day_limit":5000,"remaining_today":4404,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}