{"id":3151484,"url":"https://alion.io/job/incedo-lead-data-scientist-ml-engineering","title":"Lead Data Scientist - ML Engineering","company":{"id":177799,"name":"Incedo","domain":"incedoinc.com","url":"https://alion.io/company/incedo","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","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":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":26000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":47},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"Incident Management","optional":false},{"name":"Kubernetes","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Vertex AI","optional":false},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-10-23T11:29:46Z","employer_posted_date":null,"last_verified_at":"2026-10-23T11:29:46Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Role Overview : \n\nThis role requires a combination of advanced data science expertise, strong system design capabilities, and hands-on technical leadership. You will drive architectural decisions, guide teams through complex ML implementation challenges, and partner with business, data engineering, DevOps, cloud, and governance stakeholders to deliver production-grade AI/ML capabilities.\n\nKey Responsibilities : \n\n- Lead the architecture and implementation of end-to-end ML solutions, covering data ingestion, feature engineering, training, validation, deployment, inference, monitoring, and lifecycle management.\n\n- Translate business objectives and technical requirements into scalable ML solution designs, selecting appropriate algorithms, infrastructure, deployment patterns, and operational approaches.\n\n- Develop and optimize advanced ML models for classification, regression, forecasting, anomaly detection, and complex business use cases.\n\n- Design enterprise-grade ML pipeline architectures supporting reusable components, parallel execution, distributed processing, automated orchestration, and high-volume workloads.\n\n- Establish standards for Python application architecture, reusable libraries, API contracts, configuration management, testing, code quality, and production readiness.\n\n- Define and drive MLOps strategy, including experiment tracking, model registries, CI/CD, automated validation, release management, deployment approvals, rollback, and reproducibility.\n\n- Architect batch and real-time inference solutions, considering throughput, latency, availability, scalability, fault tolerance, and infrastructure costs.\n\n- Design comprehensive model observability frameworks covering model performance, data quality, data and model drift, service health, latency, and operational alerts.\n\n- Establish automated retraining and model promotion frameworks with appropriate validation gates, human oversight, and governance controls.\n\n- Drive performance engineering and cost optimization across data processing, model inference, compute resources, and cloud infrastructure.\n\n- Define reference architectures and reusable ML engineering frameworks that accelerate solution delivery and standardize implementation across teams.\n\n- Evaluate and guide the adoption of cloud ML platforms, distributed computing technologies, feature stores, containerization, orchestration, and model serving frameworks.\n\n- Partner with data engineering, application engineering, DevOps, security, and cloud architecture teams to ensure seamless integration with enterprise platforms.\n\n- Lead technical reviews, architecture discussions, code reviews, and root-cause analysis for complex production incidents.\n\n- Mentor data scientists and ML engineers, establish engineering best practices, and guide teams on model development, productionization, and operational excellence.\n\n- Ensure compliance with enterprise security, privacy, model governance, explainability, auditability, and responsible AI requirements.\n\n- Engage with business and technology stakeholders to communicate solution trade-offs, delivery risks, performance outcomes, and technical recommendations.\n\nRequired Skills & Expertise : \n\n- Extensive hands-on experience in Python, SQL, ML model development, and production software engineering.\n\n- Proven expertise in architecting and deploying end-to-end ML solutions in production environments.\n\n- Strong understanding of system design, distributed processing, scalable pipeline architectures, APIs, batch processing, and real-time inference.\n\n- Deep experience implementing MLOps frameworks, including experiment tracking, model registries, CI/CD, automated testing, deployment automation, and model lifecycle management.\n\n- Strong proficiency in designing reliable, reusable, configurable, and observable ML pipelines.\n\n- Experience implementing model monitoring, drift detection, automated validation, retraining strategies, and production incident management.\n\n- Demonstrated ability to optimize processing performance, inference latency, resource utilization, and cloud infrastructure costs.\n\n- Experience with cloud ML platforms such as Azure ML, AWS SageMaker, GCP Vertex AI, or Databricks.\n\n- Strong knowledge of Docker, Kubernetes, Spark/PySpark, workflow orchestration, and cloud-native deployment patterns.\n\n- Experience establishing technical standards, reviewing solution architectures, and guiding engineering teams.\n\n- Excellent stakeholder management, communication, problem-solving, and technical decision-making skills.\n\nPreferred Qualifications : \n\n- Experience building enterprise ML platforms, shared ML frameworks, feature stores, or reusable model-serving infrastructure.\n\n- Exposure to streaming architectures, distributed inference, model serving optimization, and high-availability production systems.\n\n- Experience in banking, lending, credit risk, fraud detection, financial crime, or other regulated financial services use cases.\n\n- Strong understanding of model explainability, responsible AI, model risk management, audit trails, and regulatory governance.\n\n- Experience working with cross-functional or geographically distributed teams and influencing technical strategy.\n\n- Bachelor's or master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related discipline.\n\nSkills\nData Science, Data Scientist, Machine Learning, MLOps, Python, Algorithm, Solution Design, Spark, PySpark, Cloud","description_format":"text","description_chars":5473,"description_truncated":false,"requirements":{"experience_years_min":8,"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":["Artificial Intelligence","IT Consulting & Digital Transformation","Analytics & BI Consulting","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-10-23T12:29:10Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":29,"reasons":["seen:3","velocity","win:early"],"computed_at":"2026-10-27T05:46:45Z"},"pay":null,"html_url":"https://alion.io/job/incedo-lead-data-scientist-ml-engineering","json_url":"https://alion.io/job/incedo-lead-data-scientist-ml-engineering.json","meta":{"generated_at":"2026-10-28T00:42:18Z","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":833,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-29T00:00:00Z"}},"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":177799},"rest":"https://alion.io/mcp/rest/get_company?id=177799"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fincedo-lead-data-scientist-ml-engineering"},{"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%2Fincedo-lead-data-scientist-ml-engineering"},{"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%2Fincedo-lead-data-scientist-ml-engineering"},{"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/incedo-lead-data-scientist-ml-engineering\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fincedo-lead-data-scientist-ml-engineering"}]}