Senior Data Scientist at Surveying And Mapping, LLC in Austin, Texas

Job Description:

Surveying And Mapping, LLC


Senior Data Scientist

US--

Job ID: 24-6179
Type: Regular Full-Time
# of Openings: 1
Category: Applied Technology
Continental United States

Overview

For over thirty years, SAM has built a reputation as a trusted, knowledgeable, and innovative partner. Our licensed professionals transform petabytes of complex spatial data into intelligent insights in a holistic Managed Geospatial Services™ (MGS™) framework. As North America's premiere MGS™ company, SAM provides practical, precise, and high-fidelity solutions designed to enhance decision-making, mitigate risks, achieve strategic objectives, and drive costs out of our client's business. Our vision is to advance spatial data acquisition, improve analysis capabilities, and develop predictive analytics to redefine and transform how infrastructure assets are developed and managed throughout their lifecycles.

Responsibilities

As a Senior Data Scientist, you will play a key role in driving data-driven decision-making and delivering actionable insights to drive business growth and innovation. Leveraging your expertise in data analysis, statistical modeling, and machine learning, you will lead projects that extract valuable insights from complex datasets and translate them into tangible business outcomes. The ideal cadidate must be able to perform these essential duties satisfactorily.

• Data Analysis and Modeling: Analyze large, complex datasets to identify patterns, trends, and insights that drive business decision-making. Develop and apply statistical models, machine learning algorithms, and data mining techniques to extract actionable insights from data.
• Predictive Analytics: Build predictive models to forecast future trends, behaviors, and outcomes based on historical data. Evaluate model performance and iteratively refine models to improve accuracy and effectiveness.
• Feature Engineering and Data Preparation: Engineer features and preprocess data to prepare it for analysis and modeling. Cleanse, transform, and integrate data from multiple sources to create cohesive datasets for analysis.
• Experimentation and A/B Testing: Design and analyze experiments to test hypotheses and evaluate the impact of changes on key performance metrics. Collaborate with cross-functional teams to design experiments, analyze results, and make data-driven recommendations.
• Data Visualization and Communication: Create compelling data visualizations and dashboards to communicate insights and findings to stakeholders. Present findings and recommendations in a clear and actionable manner to technical and non-technical audiences.
• Collaboration and Leadership: Lead cross-functional teams and collaborate with stakeholders across our client’s organizations to define project objectives, scope, and deliverables. Mentor junior team members and provide guidance on data science best practices and methodologies.
• Continuous Learning and Innovation: Stay abreast of the latest developments in data science, machine learning, and artificial intelligence. Identify opportunities to apply emerging technologies and methodologies to drive innovation and improve business outcomes.

Qualifications

• Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
• Proven experience as a Data Scientist or similar role, with a track record of delivering impactful data-driven solutions.
• Proficiency in programming languages such as Python or R, as well as experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).
• Strong understanding of statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with data visualization tools such as Tableau, Power BI, etc.
• Excellent problem-solving and analytical skills, with the ability to work with large and complex datasets.
• Able to communicate with clients and support sales efforts. Strong communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and communicate complex concepts to non-technical stakeholders.

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