Hitachi Solutions is a global Microsoft solutions integrator passionate about developing and delivering industry-focused solutions that support our clients to deliver on their business transformation goals. Our industry focus, expertise, and intellectual property is what truly sets us apart. We have earned, and continue to maintain, a strategic relationship with Microsoft. Recognized for our achievements - teaming with our clients to deliver innovative digital solutions and services - is how we have achieved year after year recognition.
As their trusted advisor, we support our clients to deliver on their strategic business initiatives as they unify, automate, and modernize their data and operations to increase efficiency, reduce costs, and enhance their customer's experience. Our over 3,000 team members across 14 countries, and our 18 years of 100% focus on Microsoft technologies and business applications, is how we deliver excellence through expert services and industry-focused cloud solutions.
A part of Hitachi, Ltd., our company has a long and rich history of innovation, financial strength, and international presence of one of the world's largest companies. Since 1910, Hitachi, Ltd. has been a leader in manufacturing innovative products and solutions that support industry and social infrastructure around the globe supported by 303,000 employees in over 100 countries and across 864 companies.Job Description
· Develop and code models by applying algorithms to large structured as well as unstructured data sets for our more complex projects. Develop visualization products to share analysis across a large group of business users.
· Design strategies and propose algorithms to analyze and leverage data from existing as well as new data sources.
· Continuously seek out industry best practices and develop skills to create new capabilities for data analytics at clients to improve business decisions.
· Network with business stakeholders to develop a pipeline of data science projects aligned with business strategies. Translate complex and ambiguous business problems into project charters clearly identifying technical risks and project scope.
· Participate on cross-disciplinary project team of database specialists, data scientists, and business subject-matter experts to complete project deliverables.
· Bachelor's degree from an accredited college/university in Computer Science, Computational Linguistics, Statistics, Mathematics, Engineering, Bioinformatics, Physics, Operations Research or related fields.
· Master's degree in data science, applied mathematics, or bioinformatics preferred.
· Minimum 6 years relevant work experience (if Bachelor's degree) or minimum 3 years relevant work experience (if Master's degree) with a proven track record in driving value in a commercial setting using data science skills.
· In-depth knowledge of various modeling algorithms e.g. Linear, GLMs, trees based models, neural networks, clustering, PCA, and time series models.
· Proficiency in R (e.g. ggplot2, cluster, dplyr, caret), Python (e.g. pandas, scikit-learn, bokeh, nltk), Spark - MLlib, H20, or other statistical tools.
· Minimum 2 years experience working in a data science or machine learning environment.
· In-depth knowledge of databases, data modeling, Hadoop, and distributed computing frameworks.
· Experience in software development environment, Agile, and code management/versioning (e.g. git).
· Strong EDA skills and experience/knowledge.
· Ability to understand complex and ambiguous business needs and applying the right tools and approaches.
· Collaborative team player.
· Excellent communication skills, both written and verbal.
· Experience developing and testing machine learning and/or statistical projects.
· Strong presentation skills. Ability to present statistical results to lay persons in an easy to understand way.
· We are looking for all levels of data science experience, jr through sr.QualificationsAdditional Information
We are an equal opportunity employer. All applicants will be considered for employment without attention to age, race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.