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Contract to Hire
Consulting/Contract
UG :- - Not Required
PG :- - Not Required
No of position :- ( 1 )
Post :- 14th Aug 2024
5+ years of experience in statistical analysis and machine learning within the Python ecosystem including TensorFlow, PyTorch, pandas, NumPy, and sklearn
3+ years of experience creating ML pipelines incorporating both structured and unstructured data
3+ years of experience working with various data sources including diverse file types, web service APIs, relational databases, and NoSQL
3+ years of experience implementing data science solutions on AWS, Google, or Azure cloud
Experience with supervised and unsupervised learning techniques as well as classification, regression, and anomaly detection problems
Broad understanding of machine learning including model training, hyperparameter tuning, optimization, performance evaluation, inference, model interpretability, and GPU acceleration
Experience scaling and optimizing data workloads on distributed systems
Experience working with big data file formats such as Parquet, Avro, and Iceberg
Proven ability to perform development at all stages in the data science lifecycle
Foundational understanding of software engineering, algorithms, and data structures
Familiarity with model lifecycle management and ML Ops concepts
History of continuous learning and incorporation of open data and software to solve problems
A passion for software, data, and AI
Preferred qualifications:
Master’s degree in data science or related technical field
Experience with data science on Databricks including Apache Spark and MLflow
Experience processing geospatial datasets and file formats
Experience working with time series data and sequence processing
Experience collaborating on cross-functional agile teams and presenting to key stakeholders
Foundational understanding of computer vision, NLP, and generative AI
Ability to interpret results, visualize output, and communicate data narratives to stakeholders
Working knowledge of regenerative agriculture, crop operations, and soil, plant, or climate sciences