1)            Data Scientist/ Machine Learning

Hartford, Connecticut



Kindly share the resumes with 10+ Years of Experience. Thanks



Responsibilities:

As a Data Scientist you:

Should have the ability to communicate data insights to all organizational
levels, concluding, defining recommended actions, and reporting results
across stakeholders.

Should work on integrating data from different data sources.

Should be working on pre-processing large datasets to build machine
learning models, automating, deploying, and maintaining them into
production.

Should be able to understand how the deployed models run correctly.

Should develop, test, and deploy data structures using Entity-Relationship
Diagramming, and data modeling tools.

Requirements:

1+ years of hands-on experience on Flask and Rest-API, model deployment.

3+ years of hands-on experience with Python, MySQL, and SAS (SAS
Enterprise), R, Tableau, SPSS, STATA.

5+ years of experience in data science specialization, including
statistical data analysis and/or machine learning in an enterprise-scale
environment.

Deep understanding of common database technologies, such as SQL
Database/Server, SQL Data Warehouse, Oracle, DB2, Netezza, MySQL, and other
data sources, such as Azure Data Lake Storage and Azure Blob Storage.

Experience working with distributed computing tools (Hadoop, Hive, Spark,
etc.)

Expert in Docker, CI/CD deployment, writing YMAL files to implement code
and functions as service.

Experience with Cloud Platforms using GCP/Azure/AWS.

Hands-on experience with real-time streaming processing as well as high
volume batch processing, and skilled in Advanced SQL, Amazon S3, Apache
Kafka, Data-Lakes, etc.

Experience with Tableau is a plus.

Experience with large scale data mining tools such as Spark

Advanced understanding of best practices for structuring and organizing
Data Lake file systems for large volumes of data.

Experience with ML models automation and deployment to production.

Experience performing advanced data pipelines, data structure and modeling,
data processing, data extraction, joining, manipulation cleaning, analysis,
and presentation for medium to large datasets.

Experience developing models for forecasting, classification, clustering,
regression analysis, recommendations, variable selections, and natural
language processing.

Experience with scientific computing and analysis packages such as NumPy,
Pandas, Scikit-Learn, SciPy, and ggplot2.

Experience with Deep Learning frameworks like PyTorch, TensorFlow, and
Keras.

Experience with automated feature engineering/feature extraction and
reduction.

Experience with data visualization libraries such as Matplotlib, Seaborn
Pyplot, ggplot2.

Strong grasp of experimental design, A/B testing, and advanced statistical
analysis

Experience with Git, GitHub, and Linux administration.

Experience leading end-to-end data science project implementation including
training, testing, and deploying machine learning models in production
environments.



Notes to candidates:

1.            There will be  2 Python questions and 1 SQL question.

2.            The interview will be 80% coding, 20% behavioral.

3.            The candidates are not allowed to use Google during the
interview.

4.            The candidates should test their internet connection and
camera prior to the interview.



Thanks & Regards,

Srikanth.

Direct PH: 2016233660

Email: srikant...@sparinfosys.com

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<http://sparinfosys.com/index.php>

                                             (An E-Verify Company)

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