We are hiringapioneering, fully autonomous Senior AI Engineer/Data Scientisttoown the complete data science lifecycle for our flagship prediction modelproject. This role ismission-critical— the candidate will bethe single point of expertise responsible for sourcing, analyzing, andengineering all data that powers our predictive models. Operating independentlywith minimal supervision, this individual must combinedeep AI/MLmastery, hands-on engineering skills, and sharp business acumentodeliver measurable, production-grade outcomes.
KeyResponsibilities:
DataAnalysis & Pipeline Ownership
- Lead end-to-end analysis of large, complex, multi-source datasets to surfacepatterns driving model inputs
- Identify, collect, clean, validate, and transform all data required forprediction model consumption
- Design and maintain scalable, production-grade data pipelines (training,validation, inference)
- Perform deep EDA, data profiling, and quality audits to ensure model-ready datastandards
PredictiveModeling & AI/ML
- Architect, train, evaluate, and iterate ML models — supervised, unsupervised,and reinforcement learning
- Own feature engineering: selection, extraction, transformation, anddimensionality reduction
- Apply advanced techniques: deep learning, NLP, time-series forecasting,ensemble methods
- Benchmark, A/B test, and monitor models in production; drive continuousperformance improvement
- Deploy models via REST APIs (FastAPI/Flask); ensure reproducibility andscalability
- Self-direct from problem definition through solution delivery with zerohand-holding
- Communicate model results and data insights clearly to technical andnon-technical stakeholders
- Document all experiments, methodologies, and outcomes — audit-ready andreproducible
- Champion best practices across the data science lifecycle; mentor junior teammembers
QUALIFICATIONS
- B.S./M.S./Ph.D.in Computer Science, Statistics, Mathematics, or equivalent quantitative field(Master's/Ph.D. strongly preferred)
- 5+years of hands-on data science experience with at least 2 years deliveringproduction-grade ML models
- Provenability to own and deliver end-to-end data science projects independently
- Portfoliodemonstrating innovation in predictive modeling and measurable businessimpact
- Kagglerankings, research publications, or open-source ML contributions are a strongplus
- Experiencein a fast-paced, data-driven, decision-model environment
REQUIREDSKILLS & QUALIFICATIONS
Core DataScience & Mathematics
- Statistics(Bayesian inference, hypothesis testing, regression, distributions)
- Linearalgebra, calculus, and probability applied to ML model design
- Supervised& unsupervised learning, anomaly detection, clustering
Programming& Development
- Python(Expert): NumPy, Pandas, Scikit-learn,Statsmodels,Matplotlib,Plotly
- SQL(Advanced): window functions, CTEs, query optimization
- Git/ GitHub; CI/CD for ML;MLOpswithMLflowor Kubeflow
- Docker& Kubernetes for model containerization and serving
AI / MLFrameworks (Must-Have)
- TensorFlowand/orPyTorch— deep learning architectures
- HuggingFace Transformers — NLP, LLMs, and fine-tuning
- SHAP,LIME — model explainability and interpretability
Snowflake(Good to Have)
- SnowflakeData Cloud: querying, Snowpark for Python ML pipelines
- SnowflakeCortex AI / ML Functions for in-database ML
- dbtfordata transformation; data governance within Snowflake
Kanini Software Solutions, Inc. does not discriminate in employment matters on the basis of race, gender, religion, age, national origin, citizenship, veteran status, family status, disability status, or any other protected class. We support workplace diversity. If you have a disability, please let us know if there is anything we can do to improve the interview process for you; we’re happy to accommodate. Kanini Software Solutions, Inc., 25 Century Blvd., Ste. 602, Nashville, TN 37214.
Automation, Cloud, AI-driven Insights – more than “Dreams of the Future” these have become the “Demands of the Present”, to set the stage for a business to be truly digital.