{"id":3075726,"url":"https://alion.io/job/olxcartel1-lead-data-scientist-2","title":"Lead Data Scientist","company":{"id":66068,"name":"Olxcartel1","domain":"olxcartel1.com","url":"https://alion.io/company/olxcartel1","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":"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":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"MLFlow","optional":true},{"name":"NLP","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-22T10:35:30Z","employer_posted_date":null,"last_verified_at":"2026-10-22T10:35:30Z","board_verified":false,"closed_at":null,"days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"Design, build, and productionize AI solutions, especially LLM and generative AI workloads, on top of our Enterprise data platform (Databricks, Azure, OpenAI, and AWS). This role has an emphasis on the operationalization of AI solutions, ensuring AI products are reliable, scalable, secure, and cost-effective. Effective in production. You will partner with data engineering, data science, and product teams to turn ideas into robust, continuously running services.\n\nResponsibilities: \nLead high-impact analytical and modelling projects from problem definition to measurable business outcome.\nTranslate ambiguous commercial questions into well-structured statistical or optimization problems.\nDesign and run robust analyses, including hypothesis testing, experimental design (A/B and quasi-experimental), power calculations, model validation, and backtesting.\nBuild predictive and prescriptive models using appropriate statistical and machine-learning methods.\nCritically assess model assumptions, bias/variance trade-offs, overfitting risks, and data limitations.\nClearly communicate uncertainty, limitations, and trade-offs to non-technical stakeholders.\nPartner with engineering teams to ensure models are implemented reliably and responsibly in production.\nContribute to our standards for validation, documentation, and reproducible analytical practice.\nMentor the junior members of the team.\n\nRequirements: \n7+ years of software and data science experience.\nStrong foundations in statistics and probability, including hypothesis testing and confidence intervals, regression modelling, and diagnostics.\nExperimental design and causal reasoning.\nUnderstanding of sampling, bias, variance, and uncertainty.\nDemonstrable experience applying statistical or ML models to real business problems.\nAbility to explain: Why a model works, when it won't work, what assumptions it relies on, and how confident we should be in its outputs.\nStrong Python skills (e. g., pandas, scikit-learn, PySpark, or similar) and solid SQL capability.\nExperience validating models properly (cross-validation, holdouts, backtesting, sensitivity analysis).\nClear and confident communication with both technical and non-technical stakeholders.\nA degree (or equivalent experience) in statistics, mathematics, computer science, engineering, or a related quantitative field.\nWe value candidates who can reason deeply about a problem, not just apply a library.\n\nPreferred Qualifications: \nStrong communication skills and stakeholder management skills.\nInnovative mindset and a go-getter attitude.\nExperience with optimization methods or operations research.\nExposure to causal inference techniques (e. g., matching, uplift modelling, diff-in-diff).\nExperience applying NLP or GenAI in a statistically responsible way.\nFamiliarity with model lifecycle tools (e. g., MLflow, Databricks).\n\nBehavioral Competencies: \nLead initiatives with high accountability and create a collaborative environment with a solution-based approach.\nServe as a trusted advisor and mentor for the team, offering technical advice.\nAbility to communicate with precision, engaging the team and stakeholders to build trust and reliable working relationships across cross-functional teams and geographies, enabling organizational alignment.\nAbility to set priorities with the team by understanding interdependence and inspiring team members with consistent focus, quality output, and timelines.\nConstantly keep oneself updated on current technology & trends to drive innovative decisions through piloting forward-thinking approaches to complex problems in one's own area of work.\nInquisitive to understand customer priorities and business challenges while creating value for technical solutions.\nSkills\nML, PySpark, Python, causal inference, experimental design, machine learning, probability, regression, scikit-learn, statistics","description_format":"text","description_chars":3869,"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":["iGaming & 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