SHI International Corp.

Data Scientist

Python Machine Learning Bayesian

January 11, 2022

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Milton Keynes MK9, United Kingdom

January 11, 2022

Apply Now

Job description

Job Summary:

The Data Scientist is passionate about using data science to enhance customer experience, identify sales opportunities, improve business operations, and recommend high value sales motions with a high probability of success. The role requires in-depth and hands-on knowledge of advanced analytics practices and approaches including Machine Learning & Artificial Intelligence and the creativity to discuss innovation opportunities with business partners and shape cutting edge applications and proposals.

The Data Scientist must be comfortable working in a multidisciplinary environment to drive business solutions. Additionally, the Data Scientist will meet with executive/c-suite team members to present findings and make recommendations based on project outcomes.

About Us:

Founded in 1989, SHI International is a global IT solutions provider, with a projected 2020 revenue of $11 billion. SHI currently has 5,000 employees worldwide.

To learn more about SHI International Corp, visit our website: www.shi.com/careers

What SHI Can Offer:

World Class Facility includes on site gyms and cafeterias
Ongoing opportunities for personal and professional growth and development due to our strong promote from within philosophy
Work in an up-beat, creative, and fun environment
Benefits including medical, vision, dental, 401K, and flexible spending

Responsibilities:

Include but not limited to:

Lead and participate in highly visible, complex, data-driven research projects that have a direct impact on SHI’s business
Explore the space of analytical solutions for a given problem and execute with a sound strategy
Acquire, analyze, and act on complex, high-dimensional data sets using appropriate statistical/machine learning approaches

Gather and integrate data; create ETL (Extract, transform & load) jobs
Explore, inspect, and clean data; engineer features
Train, validate, and test statistical/machine learning models
Deploy and maintain statistical/machine learning model-based applications and services

Organize and lead meetings with internal stakeholders to present and discuss project objectives, timelines, progress, and outcomes
Collaborate and coordinate with internal groups, as needed, to accomplish project objectives
Maintain up-to-date working knowledge in relevant areas of data science, statistics, machine learning, and artificial intelligence

Qualifications:

Masters degree or PhD in Data Science, Computer Science, Statistics or related quantitative discipline
5 years of work experience (which can include post-doctoral work) as a data scientist, statistician, machine learning engineer, or equivalent role
Strong working knowledge of data science, statistics, and machine learning theory, algorithms, and applications, covering:

Unsupervised learning (dimensionality reduction and clustering)
Supervised learning (regression and classification)
Multiple model types (linear models, generalized linear models, trees, neural networks, ensembles)
Multiple inference methods (maximum likelihood, Bayesian, approximate Bayesian)
Workflows (exploratory data analysis; model training, validation, and testing)

Experience with most phases of a data science project:

Data gathering
Data inspection, cleaning, preprocessing
Exploratory data analysis
Statistical or machine learning model fitting, validation, and testing
Model deployment and maintenance
Data visualization and communication of findings

Required Skills:

Ability to work with large datasets (millions of observations)
Skilled in one or more programming languages such as Python
Familiarity with a cloud computing platform such as Amazon Web Services
Excellent communication, interpersonal, verbal, and written skills
Strong public speaking and presentation skills
Ability to keep pace with rapidly evolving knowledge, technology, and industry practices
Ability to adapt to changing priorities and unforeseen challenges

Preferred Skills/Qualifications:

Programming languages: Python and SQL
Cloud computing platform: Amazon Web Services (Sagemaker, Glue, Lambda, API Gateway)
Machine learning and statistics tools (any of): Scikit-learn, Statsmodels, Tensorflow, Torch, Stan, PyMC3, or Amazon Sagemaker
Experience with natural language processing
Experience with recommender systems
Experience with forecasting
Experience with A/B testing
Experience with sales data
Experience with bespoke statistical modeling

Unique Requirements: