What're Looking For We are looking for a
Senior Data Scientist II to join our Data Science team and help design, develop, evaluate, and productionize AI and machine learning capabilities that improve our products and customer experiences.
This is a senior individual-contributor role for someone who combines strong data science fundamentals with hands-on engineering ability. The successful candidate will take ownership of complex data science initiatives from problem definition and experimentation through implementation, evaluation, and production delivery, while collaborating closely with Product Management, Software Development, QA, and other stakeholders.
The existing internal Senior Data Scientist 2 profile emphasizes end-to-end ML and analytics ownership, cross-functional product collaboration, and oversight of junior data scientists.
What You'll Do- Graduate degree in Computer Science, Software Engineering, Data Science, Statistics, Mathematics, or another quantitative discipline, or equivalent relevant industry experience.
- Lead end-to-end AI/ML initiatives, from problem formulation, data analysis and experimentation through model development, evaluation, deployment, and ongoing improvement.
- Develop innovative and effective solutions using machine learning, statistical modeling, predictive analytics, NLP, and modern AI techniques.
- Build robust evaluation methodologies and metrics to measure model quality, accuracy, reliability, and product impact.
- Analyze structured and unstructured datasets, performing data profiling, cleaning, feature engineering, exploratory analysis, and validation.
- Write production-quality Python code and work closely with software development teams to integrate data science capabilities into customer-facing products.
- Research, define, prototype, and develop new data science and AI capabilities that can become part of the product experience.
- Collaborate closely with Product Management, Development, QA, and other business stakeholders to translate ambiguous product or customer problems into measurable data science problems and solutions.
- Take ownership of complex projects with limited supervision, driving them from investigation to production-ready outcomes.
- Diagnose model and data-quality issues, investigate unexpected behavior, reproduce problems, perform root-cause analysis, and recommend practical improvements.
- Apply appropriate techniques across areas such as NLP, classification, predictive modeling, anomaly detection, time-series analysis, and forecasting.
- Stay current with developments in machine learning and AI, identifying techniques that have practical value for our products rather than adopting technology solely for novelty.
- Communicate technical approaches, experimental results, limitations, and recommendations clearly to both technical and non-technical stakeholders.
- Provide technical guidance and mentorship to other data scientists and contribute to strong engineering, experimentation, documentation, and review practices across the team.
Experience You'll Bring- 5+ years of professional experience building machine learning or applied data science solutions. This aligns with your existing Senior Data Scientist 2 level.
- Expert-level Python skills, including the ability to develop clean, maintainable, production-ready code.
- 1 yr+ experience in Multi Agentic, MCP based production grade AI systems development.
- 3+ years of production experience with NLP, classification, predictive modeling, or related machine learning techniques.
- Strong understanding of statistical modeling, machine learning algorithms, experimentation, model evaluation, and the ability to choose appropriate methods for real-world problems.
- Strong data profiling, cleaning, mining, debugging, and technical documentation skills.
- Experience building AI/ML solutions using cloud infrastructure such as Microsoft Azure or AWS.
- Experience taking models beyond notebooks and prototypes into production environments.
- Strong analytical troubleshooting skills, including the ability to reproduce issues, isolate data/model failures, and perform root-cause analysis.
- Ability to communicate complex technical findings clearly and work effectively with Data Science, Development, Product, and QA teams.
- Keep abreast with latest happenings in AI domain.
Strong Assets- Experience with Generative AI, LLMs, Retrieval-Augmented Generation (RAG), embeddings, semantic retrieval, or AI-agent applications.
- Experience establishing repeatable model evaluation and benchmarking frameworks.
- Knowledge of MLOps, including CI/CD, model monitoring, model/version management, production metrics, and rollback strategies. These practices also appear in the broader Data Science leadership expectations documented internally.
- Experience with deep-learning architectures, including Transformers, sequence models, CNNs, or related architectures, which is part of the existing Senior Data Scientist 2 requirements.
- 2+ years of experience with time-series analysis, forecasting, or anomaly detection, consistent with the current profile
- Experience mentoring other data scientists or providing technical leadership on complex projects.
What Success Looks LikeA strong Senior Data Scientist II on your team should be able to:
- Take an ambiguous product/customer problem and turn it into a measurable ML problem.
- Independently investigate the data and establish a credible evaluation methodology.
- Develop and compare practical approaches rather than stopping at a research prototype.
- Produce maintainable, production-quality Python.
- Work effectively with developers to get the capability into the product.
- Diagnose failures using data and evidence and improve the solution iteratively.
- Explain trade-offs and results clearly to Product, Development, QA, and Data Science stakeholders.
- Raise the technical capability of the team through reviews, mentorship, and reusable practices.
