Senior Data ScientistDescription - External
Primary Responsibilities:
Drive client value by:
oDeveloping predictive models using various machine learning algorithms/best practices
oDeveloping and running scripts for ML model inference
oTesting various hypothesis and presenting back to the technical/non-technical audience
oResponsible for performing cost benefit analysis for various DS initiatives
oDesign, implement, and maintain CI/CD pipelines for MLOps and DevOps functions
oCreating artifacts like STM, HLD, LLD for hardening prototypes into production (prototype to hardening)
oApplying knowledge of data modeling, statistics, machine learning, programming, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to more actionable insights
oWorking with analytics and statistical software and products, such as SQL, R, Python, Hadoop and others to perform analysis and interpret data
oCommunicate the performance of the machine learning algorithms across an interdisciplinary team.
Create impact at scale by:
oDeveloping and managing a comprehensive catalog of scalable data services that expand the value of analytical offerings
oLooking for opportunities for continuous improvement/optimization of models in production.
Data Drift
Champion (Prod Model) Vs Challenger (Enhanced Dev Model)
oResponsible for implementing best practices on ML architecture/workflows etc
oCollaborating with business intelligence architects and domain analysts to maximize the effectiveness of business intelligence tools, dashboards, and other dynamic reporting capabilities
Qualifications - External
- Undergraduate degree or equivalent experience.
Required Qualifications:
Bachelors Degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)
Highly proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages.
Minimum of 5+ years of experience in handling/active development in data science projects.
Minimum of 5+ years of experience in Microsoft Azure Cloud, Databricks, Mlflow, Spark SQL & Python.
Experience using Machine Learning Algorithms: Linear & Logistic Regression, Time Series analysis, Support Vector Machine, K-Means clustering, K-Nearest Neighbors Decision Trees, Random Forest, Naive Bayes, PCA, SVD, Artificial Neural Networks, Association Rules, Genetic Algorithm, Optimization, Bagging and Boosting algorithms etc.
Understanding for data, schema, data model, machine learning and how to bring efficiency in big data related life cycle
Skills to create opportunities using machine learning or artificial intelligence

Keyskills: data scientist Python Data Science Azure SQL
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