Senior Data Scientist (Business Analytics)

Senior Data Scientist (Business Analytics)
Company:

Stefanini, Inc.


Senior Data Scientist (Business Analytics)

Details of the offer

Stefanini Group is hiring!

We are looking for a Senior Data Scientists who will work within the Business Analytics & Data Services department and reports through the CIO. They play a pivotal role in the planning, execution and delivery of data science and machine learning and AI based projects. The bulk of the work will be in areas of data exploration and preparation, data collection and integration, machine learning (ML) and statistical modelling. It is expected that successful candidates will be able to perform their job duties with little to no technical guidance. They will also be expected to mentor less technical data resources to help grow our data literacy as an organization.

Responsibilities:

Problem Analysis and Project Management:

Guide and inspire the organization about the business potential and strategy of artificial intelligence (AI)/data science

Identify data-driven/ML business opportunities

Collaborate across the business to understand IT and business constraints

Prioritize, scope and manage data science projects and the corresponding key performance indicators (KPIs) for success

Data Exploration and Preparation:

Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA)

Generate and test hypotheses about the underlying mechanics of the business process.

Network with domain experts to better understand the business mechanics that generated the data.

Data Collection and Integration:

Understand new data sources and process pipelines. Catalog and document their use in solving business problems.

Create data pipelines and assets the enable more efficiency and repeatability of data science activities.

Data Exploration and Preparation:

Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA)

Machine Learning and Statistical Modelling:

Apply various ML and advanced analytics techniques to perform classification or prediction tasks

Integrate domain knowledge into the ML solution; for example, from an understanding of financial risk, customer journey, quality prediction, sales, marketing

Testing of ML models, such as cross-validation, A/B testing, bias and fairness

Operationalization:

Collaborate with ML operations (MLOps), data engineers, and IT to evaluate and implement ML deployment options

(Help to) integrate model performance management tools into the current business infrastructure

(Help to) implement champion/challenger test (A/B tests) on production systems

Continuously monitor execution and health of production ML models

Establish best practices around ML production infrastructure

Other Responsibilities:

Train other business and IT staff on basic data science principles and techniques

Train peers on specialist data science topics

Promote collaboration with the data science COE within the organization.

A bachelor s degree in computer science, data science, operations research, statistics, applied mathematics, or a related quantitative field [or equivalent work experience such as, economics, engineering and physics] is required. Alternate experience and education in equivalent areas such as economics, engineering or physics, is acceptable. Experience in more than one area is strongly preferred.

Candidates should have 8-10 years of relevant project experience in successfully launching, planning, executing] data science projects. Preferably in the domains of automotive or customer behavior prediction.

Coding knowledge and experience in several languages: for example, R, Python, SQL, Java, C++, etc.

Knowledge and experience in statistical and data mining techniques: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.

A specialization in text analytics, image recognition, graph analysis or other specialized ML techniques such as deep learning, etc., is preferred.

Experience of working across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service, and others.

Experience with distributed data/computing and database tools: MapReduce, Hadoop, Hive, Kafka, MySQL, Postgres, DB2 or Greenplum, etc.

They must demonstrate the ability to work in diverse, cross-functional teams.

Should be confident, energetic self-starters, with strong moderation and communication skills.

Skills & Experience Preferred:

Master s degree and above is preferred

Experience using Keras TensorFlow is big bonus

Required: Bachelor's degree in a related field is required.

Interested applicants may click the apply button or you may call us at (248) 936-0629 for faster processing. Thank you.


Source: Dice


Area:

Requirements


Knowledges:

  • Basic
  • DB2

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