K
Senior AI Engineer/Data Scientist
KANINI Software Solutions PTE Ltd.
3 hours ago
Full-time
On-site
Nashville, Tennessee, United States
We are hiringa pioneering, fully autonomous Senior AI Engineer/Data Scientist toown the complete data science lifecycle for our flagship prediction modelproject. This role is mission-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 combine deep AI/MLmastery, hands-on engineering skills, and sharp business acumen todeliver 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.
#J-18808-Ljbffr
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.
#J-18808-Ljbffr