Data Scientist (Bangalore, KA, IN, 560 029)

Ingersoll Rand
Bengaluru
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 4-5 yearsEducation: bachelorsSkills: ["Collaboration","Stakeholder communication","Ownership mindset","Code review","Analytical validation"]

Own the full MLOps lifecycle for reliable ML deployment and insights governance. Build CI/CD pipelines for ML models, enforce data quality standards, and validate outputs for statistical soundness before stakeholders receive results. Set up monitoring for drift and performance, trigger automated retraining, and develop production-grade time-series and fault-detection pipelines using large-scale IoT sensor datasets. Partner cross-functionally to translate requirements into scalable ML solutions on GCP.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Ingersoll Rand
Ingersoll Rand
2 months ago

Data Scientist (Bangalore, KA, IN, 560 029)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Own the full MLOps lifecycle for reliable ML deployment and insights governance. Build CI/CD pipelines for ML models, enforce data quality standards, and validate outputs for statistical soundness before stakeholders receive results. Set up monitoring for drift and performance, trigger automated retraining, and develop production-grade time-series and fault-detection pipelines using large-scale IoT sensor datasets. Partner cross-functionally to translate requirements into scalable ML solutions on GCP.
Location: Bengaluru
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Own the end-to-end MLOps lifecycle, including model packaging, versioning, cloud deployment, monitoring, and automated retraining pipelines on GCP using Vertex AI, MLflow, or Kubeflow.
  • •Design and maintain CI/CD pipelines for ML models with reliable, repeatable deployments and full model registry traceability.
  • •Define and enforce data quality governance standards across ML feature pipelines and training datasets, including schema contracts and validation checks.
  • •Validate model outputs and analytical findings for statistical soundness and insights validation (data leakage, bias, distributional assumptions, reproducibility) before results reach stakeholders.
  • •Set up model monitoring for prediction drift, data drift, and performance degradation, triggering automated retraining workflows when thresholds are breached.

Pay and Benefits

Equity and Bonus:Equity
Perks:EquityAnnual BonusLeave EncashmentMaternity/paternityHealth InsuranceLife InsuranceAccident InsuranceEmployee AssistanceLearning BudgetEmployee Recognition

Key Requirements

  • •Own the end-to-end MLOps lifecycle, including CI/CD for ML, model versioning, deployment automation, monitoring, and retraining pipelines on GCP (Vertex AI) or AWS (SageMaker).
  • •Advanced SQL skills for writing and reviewing optimized, cost-efficient queries (partitioning, clustering, query plan analysis, scalable transformations) for large-scale workloads.
  • •Strong Python skills for production-grade ML code, including feature engineering, batch scoring, and inference pipelines using scikit-learn, TensorFlow, PyTorch, or Pandas.
  • •Hands-on implementation of data quality governance (schema contracts, automated profiling, pipeline-level validation, lineage tracking, and quality scorecards).
  • •Ability to validate insights statistically (data leakage, biased evaluations, distributional shifts, and reproducibility) before stakeholder delivery.
Experience:4-5 yearsManufacturingIoTPredictive maintenanceIndustrial machineryTime-series
Education:Bachelor's in Computer Science or Data Science or Artificial Intelligence or Electrical / Mechanical Engineering
Skills:CollaborationStakeholder communicationOwnership mindsetCode reviewAnalytical validation
Certifications:Google Professional ML EngineerAWS ML Specialty
Tech Stack:PythonSQLBigQueryGCPVertex AIMLflowKubeflowCI/CDScikit-learnTensorFlowPyTorchPandasGitHub CopilotClaudeGitDbtAWSSageMakerInfluxDBTimescaleDB

Company Brief

Ingersoll Rand
Designs, manufactures, and services industrial equipment and technologies including air compressors, power tools, fluid management systems, and downstream industrial solutions for manufacturing, construction, and commercial customers worldwide.
Industry: Industrial Machinery
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Davidson, United States
Founded: 1871
WebsiteLinkedIn