About this opportunity
KANINI lists this Data Scientist opportunity in nashville, Tennessee. Review the employer’s description below for duties, qualifications and application requirements.
Job description
We are hiring a pioneering, fully autonomous Senior Data Scientist to own the complete data science lifecycle for our flagship prediction model project. This role is mission-critical — the candidate will be the single point of expertise responsible for sourcing, analyzing, and engineering all data that powers our predictive models. Operating independently with minimal supervision, this individual must combine deep AI/ML mastery, hands‑on engineering skills, and sharp business acumen to deliver measurable, production‑grade outcomes.
Key Responsibilities:
Data Analysis & Pipeline Ownership
Lead end-to-end analysis of large, complex, multi-source datasets to surface patterns driving model inputs
Identify, collect, clean, validate, and transform all data required for prediction 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 data standards
Predictive Modeling & AI/ML
Architect, train, evaluate, and iterate ML models — supervised, unsupervised, and reinforcement learning
Own feature engineering: selection, extraction, transformation, and dimensionality reduction
Apply advanced techniques: deep learning, NLP, time‑series forecasting, ensemble methods
Benchmark, A/B test, and monitor models in production; drive continuous performance improvement
Deploy models via REST APIs (FastAPI/Flask); ensure reproducibility and scalability
Self‑direct from problem definition through solution delivery with zero hand‑holding
Translate ambiguous business problems into precise, executable data science problem statements
Communicate model results and data insights clearly to technical and non‑technical stakeholders
Document all experiments, methodologies, and outcomes — audit‑ready and reproducible
Champion best practices across the data science lifecycle; mentor junior team members
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 delivering production‑grade ML models
Proven ability to own and deliver end‑to‑end data science projects independently
Portfolio demonstrating innovation in predictive modeling and measurable business impact
Experience in a fast‑paced, data‑driven, decision‑model environment
REQUIRED SKILLS & QUALIFICATIONS
Core Data Science & Mathematics
Statistics (Bayesian inference, hypothesis testing, regression, distributions)
Linear algebra, calculus, and probability applied to ML model design
Supervised & unsupervised learning, anomaly detection, clustering
Time‑series analysis & forecasting: ARIMA, Prophet, LSTM
Programming & Development
SQL (Advanced): window functions, CTEs, query optimization
Git / GitHub; CI/CD for ML; MLOps with MLflow or Kubeflow
Docker & Kubernetes for model containerization and serving
AI / ML Frameworks (Must-Have)
TensorFlow and/or PyTorch — deep learning architectures
Hugging Face Transformers — NLP, LLMs, and fine‑tuning
SHAP, LIME — model explainability and interpretability
Snowflake (Good to Have)
Snowflake Data Cloud: querying, Snowpark for Python ML pipelines
Snowflake Cortex AI / ML Functions for in‑database ML
dbt for data transformation; data governance within Snowflake
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Worksite address
nashville, TN, 37247, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.