DATA
SCIENTIST
Behind every software platform is a mountain of data that possesses an enormous amount of value, some of which needs to be mined, designed, and refined. Continuously creating unique, business critical products for our clients is a mission that we take seriously. We are eager to add another data scientist to our team who adopts this mission as their own while exploring new ways to view and present information.
LOCATION
Houston
EMPLOYMENT TYPE
Permanent
What You’ll Do
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Data Analysis: Analyzing large datasets to identify trends, patterns, and insights using statistical methods and machine learning algorithms.
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Model Development: Developing predictive models and machine learning algorithms to solve specific business problems and improve decision-making processes.
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Data Cleaning and Preparation: Cleaning, transforming, and preprocessing data to ensure its quality, accuracy, and suitability for analysis and modeling.
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Data Visualization: Creating clear and compelling data visualizations to communicate findings and insights to both technical and non-technical stakeholders.
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Collaboration: Collaborating with cross-functional teams, including business analysts, engineers, and decision-makers, to understand their data-related requirements and provide data-driven solutions.
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Continuous Learning: Staying updated with the latest advancements in data science, machine learning techniques, and relevant tools to enhance skills and contribute effectively to projects.
Who You are
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Database Knowledge: Familiarity with databases and query languages (e.g., SQL) for extracting and manipulating data from various data sources.
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Data Visualization: Experience in data visualization tools like Tableau, D3.js, or Matplotlib to present data-driven insights effectively to stakeholders.
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Analytical Skills: Strong analytical skills to interpret complex data sets and extract meaningful insights. Proficiency in statistical analysis and machine learning techniques is essential.
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Programming Skills: Proficiency in programming languages such as Python, R, or Java, and familiarity with libraries like TensorFlow, PyTorch, or scikit-learn for data manipulation and machine learning tasks.
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Communication Skills: Strong communication skills to explain complex analytical concepts and findings to both technical and non-technical audiences. Additionally, the ability to work in multidisciplinary teams and collaborate effectively.