{"id":3271766,"url":"https://alion.io/job/sigmoid-lead-data-scientist","title":"Lead Data Scientist","company":{"id":1528,"name":"Sigmoid","domain":"sigmoid.com","url":"https://alion.io/company/sigmoid","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":68,"open_postings":34,"ghost_share":0.529,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":39,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"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":null,"salary_estimate":{"min_usd":31000,"max_usd":66000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":20},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BERT","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"WhatsApp","optional":true}],"status":"live","first_seen_at":"2021-11-02T08:27:13Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-28T15:34:50Z","board_verified":true,"closed_at":null,"days_open":1821,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":1820},"description":"Work Experience: 8+ years\nMandate Skills:\nExperience in Programing (Python, R, SQL, NoSQL,Spark) with ML tools & Cloud Technology (AWS, Azure, GCP)\nExperience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc.\nGood understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making.\nDevelops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.)\nEngaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc.\nContribute to internal product development initiatives related to data science.\nDevelop data science roadmap, and guide data scientist to meet their deliverables.\nHandling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.\nProven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights\nDrive excellent project management required to deliver complex projects, including effort/time estimation.\nBe proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy\nDefine Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects\nRun regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders\nManage the team-members, to ensure that the project plan is being adhered to over the course of the project\nManage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates.\nBuild a trusted advisor relationship with the IT management at clients and internal accounts leadership.\nBuild business case for technological investments to be made for future needs and to remain competitive\nEnsure that billing and utilization of team members is maximized throughout the year\nDesired Skills:\nExperience designing data science solutions to business problems\nDeep understanding of ML algorithms for common 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