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Posted: 10/21/2026Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in translating business problems into data science solutions, with a strong focus on statistical modeling, machine learning, and MLOps practices. Proven ability to mentor teams, collaborate across time zones, and uphold responsible AI standards.
Highest-signal resume keywords
Data Science SolutionsMachine LearningPythonSQLMLOps
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Translate ambiguous business problems into well-scoped data science solutions with clear success metrics
- Design end-to-end solutions from data requirements and modeling approach through deployment and monitoring
- Build reference implementations, reusable components and templates
- Make build, buy and reuse decisions while balancing accuracy, cost, speed and maintainability
- Write design documents, runbooks and code standards
- Review code, models and experiments for quality and reproducibility
- Mentor data scientists and ML engineers and run knowledge-sharing sessions
- Hand over solutions and unblock teams through delivery
- Collaborate with onshore and offshore teams across time zones
- Run design reviews and planning sessions with clear written decisions
- Apply statistical modeling, machine learning and forecasting to prediction, optimization and segmentation problems
- Prototype GenAI use cases and take proven solutions to production
- Define evaluation methods for models and LLM output, including accuracy, bias, drift and cost
- Advise senior leaders on data science capabilities and limitations
- Work with data engineering and platform teams on pipelines, MLOps and model monitoring
- Uphold responsible-AI, privacy and security standards
Requirements
What you’ll need- Bachelor's or Master's in Data Science, Statistics, Computer Science, Mathematics or a related quantitative field (or a bachelor's with equivalent experience)
- 9+ years in data science or applied machine learning, with a record of solutions running in production
- Strong Python and SQL; experience with scikit-learn, pandas, PyTorch or TensorFlow
- Deep knowledge of statistics, experimental design and supervised, unsupervised, time series and NLP techniques
- Experience designing solutions implemented and maintained by other teams, with documented patterns and handoff
- Experience leading or mentoring data scientists and engineers, formally or as a technical lead
- Experience working with distributed teams across time zones
- Clear communication with technical teams and business executives
- Preferred: hands-on LLM experience, including prompt design, RAG, fine-tuning and output evaluation
- Preferred: MLOps experience, including model versioning, CI/CD for ML, monitoring and retraining
- Preferred: experience with Snowflake, Databricks, BigQuery or Microsoft Fabric
- Preferred: familiarity with Spark or other distributed processing frameworks
- Preferred: healthcare industry experience
- Preferred: publications, patents or open-source contributions
- Preferred: relevant cloud or ML certifications
Benefits
Comp & perks- Annual bonus
- Benefits information provided at https://www.exlservice.com/us-careers-and-benefits
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistical ModelingExperimental DesignSupervised LearningUnsupervised LearningTime Series AnalysisNatural Language ProcessingModel MonitoringData RequirementsDeploymentForecasting
Soft Skills
Clear CommunicationMentoringCollaboration
Tools & Technologies
Scikit-LearnPandasPyTorchTensorFlowSnowflakeDatabricksBigQueryMicrosoft FabricSpark
Certifications & Qualifications
Relevant Cloud CertificationsML Certifications
Industry Keywords
Healthcare Industry ExperienceResponsible AIPrivacy StandardsSecurity Standards