Data Ops
2 weeks ago
Job Description:
Excellent data science skills -hands on knowledge of new data science technologies ?
5+ years of experience leveraging quantitative analysis, analytics, and data science to solve business problems, preferably within a large operation, customer service. ?
Experience with scientific/statistical languages such as R or Python ?
Experience in building competitive business models in areas such as Marketing Analytics, HR Analytics, Customer 360, Supply Chain Operational Analytics, Price Optimization, Competitive Intelligence etc. ?
Experience working directly with business teams to drive results ?
Experience in building and operationalizing algorithms, predictive models, graph models and statistical techniques with varying types of data models to use various variables to prove business models that drive growth and efficiency. ?
Knowledge and experience in organizing data to drive operational models ?
Excellent understanding of Machine Learning (Supervised, Unsupervised, Recommendation engines, Optimization etc.)
Deep Learning (RNN, CNN, LSTM, Auto encoders, GANS etc.), Natural Language Processing techniques and algorithms ?
Experience with NoSQL databases, such as MongoDB/Cassandra/HBase etc. ?
Proven ability of working on open source frameworks such as Keras, TensorFlow, SparkML, H20 etc. ?
Experience of working on AWS cloud platform and nice to have experience with Azure as well. ? Designing and implementing high performance end to end streaming and batch data analytics pipelines using Databricks from data ingestion, processing, storage, analysis to visualization ?
Extensive experience in model development and life-cycle-management in one or more industries. ?
Work closely with data engineers to source, analyze and engineer features, collaborate with fellow data scientists to develop, test and deploy Machine Learning models ?
Keep up to speed with the latest industry and technology developments on Machine Learning ?
Doing ad-hoc analysis and presenting results in a clear manner ?
Exposure to creation of data pipelines to engineer apps deployment (CI/CD) across platforms and environments and working with ML pipelines
**Job Types**: Full-time, Permanent
**Experience**:
- Data Ops: 5 years (preferred)
Work Location: In person
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