Trace3, Inc.
Sr. Data Scientist | San Antonio, TX
Trace3, Inc., San Antonio, Texas, United States, 78208
Position Summary
We are seeking a highly skilled and experienced Sr. Data Scientist to join our dynamic Data Science and AI team. In this role, you will be instrumental in transforming data into actionable insights and innovative solutions, driving forward our business strategy. You will leverage advanced machine learning, statistical techniques, and analytical prowess to solve complex business challenges, collaborating closely with cross-functional teams to design, develop, and deploy scalable AI-driven models and algorithms.
This position belongs to a family of jobs with increasing responsibility, competency, and skill level. Actual position title and pay grade will be based on the selected candidate’s experience and qualifications.
Key Responsibilities
Engage in the ideation and prototyping of new solutions to meet emerging business requirements.
Utilize advanced machine learning techniques (e.g., deep learning, NLP, computer vision, reinforcement learning) to create innovative solutions.
Lead multiple data science projects ensuring alignment with business goals.
Develop predictive models and integrate them with Business Intelligence tools. Optimize model performance, addressing issues such as overfitting, underfitting, and bias.
Develop and maintain data pipelines for efficient data retrieval and processing. Collaborate with applications and data engineering teams for deploying models at scale.
Mentor junior data scientists in model development and data handling.
Engage with Senior Leadership to inform strategic decisions using business intelligence insights.
Research and adopt cutting-edge technologies and methodologies in data science.
Perform exploratory data analysis to identify patterns, insights, and communicate findings.
Manage stakeholder expectations and deliver actionable solutions.
Oversee data processing pipelines ensuring data quality and consistency.
Drive ethical considerations in model deployment and data utilization.
Collaborate with external partners, research institutions, and subject matter experts to gather domain-specific knowledge and datasets.
Education and Experience
Bachelor’s Degree in Information Technology, related field or equivalent experience preferred.
Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field preferred.
5+ years of relevant experience required.
Expertise in Python and proficiency in ML frameworks (TensorFlow, PyTorch, scikit-learn).
Deep understanding of ML algorithms (supervised, unsupervised learning, and deep learning) and their applications.
Strong problem-solving, critical thinking, and analytical capabilities.
Skills
Artificial Intelligence (AI) and Machine Learning (ML)
- Understanding of AI/ML concepts, algorithms, and platforms to design architectures that support intelligent systems and enable AI-driven applications.
Business Domain Knowledge
- Understanding of business processes, industry trends, and market dynamics to provide relevant and actionable insights for strategic decision-making.
Communication and Collaboration
- Excellent communication skills to effectively interact with stakeholders, gather requirements, present architectural proposals, and collaborate with cross-functional teams.
Data Analysis
- The process of measuring and managing organizational data, identifying methodological best practices, and conducting statistical analyses.
Data Ethics & Responsible Innovation
- Knowledge of ethical considerations related to data usage, data-driven technologies, and strategies to mitigate biases in data-driven decision-making.
Data Mining and Extraction
- Data mining is sorting through data to identify patterns and establish relationships.
Data Monetization and Data Science
- Familiarity with data monetization strategies and techniques, such as data commercialization, data marketplaces, and data value realization.
Natural Language Processing
- Proficiency in analyzing and extracting insights from unstructured text data, including sentiment analysis, topic modeling, and language understanding.
Problem-Solving and Analytical Thinking
- Strong problem-solving skills to identify architectural challenges, analyze requirements, evaluate options, and propose effective solutions.
Reporting and Dashboarding
- The ability to access information from databases, forms, and other sources, and prepare reports according to requirements.
Statistical Analysis
- Statistical analysis is used in support of decision-making and includes fundamental principles such as data collection and sampling.
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We are seeking a highly skilled and experienced Sr. Data Scientist to join our dynamic Data Science and AI team. In this role, you will be instrumental in transforming data into actionable insights and innovative solutions, driving forward our business strategy. You will leverage advanced machine learning, statistical techniques, and analytical prowess to solve complex business challenges, collaborating closely with cross-functional teams to design, develop, and deploy scalable AI-driven models and algorithms.
This position belongs to a family of jobs with increasing responsibility, competency, and skill level. Actual position title and pay grade will be based on the selected candidate’s experience and qualifications.
Key Responsibilities
Engage in the ideation and prototyping of new solutions to meet emerging business requirements.
Utilize advanced machine learning techniques (e.g., deep learning, NLP, computer vision, reinforcement learning) to create innovative solutions.
Lead multiple data science projects ensuring alignment with business goals.
Develop predictive models and integrate them with Business Intelligence tools. Optimize model performance, addressing issues such as overfitting, underfitting, and bias.
Develop and maintain data pipelines for efficient data retrieval and processing. Collaborate with applications and data engineering teams for deploying models at scale.
Mentor junior data scientists in model development and data handling.
Engage with Senior Leadership to inform strategic decisions using business intelligence insights.
Research and adopt cutting-edge technologies and methodologies in data science.
Perform exploratory data analysis to identify patterns, insights, and communicate findings.
Manage stakeholder expectations and deliver actionable solutions.
Oversee data processing pipelines ensuring data quality and consistency.
Drive ethical considerations in model deployment and data utilization.
Collaborate with external partners, research institutions, and subject matter experts to gather domain-specific knowledge and datasets.
Education and Experience
Bachelor’s Degree in Information Technology, related field or equivalent experience preferred.
Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field preferred.
5+ years of relevant experience required.
Expertise in Python and proficiency in ML frameworks (TensorFlow, PyTorch, scikit-learn).
Deep understanding of ML algorithms (supervised, unsupervised learning, and deep learning) and their applications.
Strong problem-solving, critical thinking, and analytical capabilities.
Skills
Artificial Intelligence (AI) and Machine Learning (ML)
- Understanding of AI/ML concepts, algorithms, and platforms to design architectures that support intelligent systems and enable AI-driven applications.
Business Domain Knowledge
- Understanding of business processes, industry trends, and market dynamics to provide relevant and actionable insights for strategic decision-making.
Communication and Collaboration
- Excellent communication skills to effectively interact with stakeholders, gather requirements, present architectural proposals, and collaborate with cross-functional teams.
Data Analysis
- The process of measuring and managing organizational data, identifying methodological best practices, and conducting statistical analyses.
Data Ethics & Responsible Innovation
- Knowledge of ethical considerations related to data usage, data-driven technologies, and strategies to mitigate biases in data-driven decision-making.
Data Mining and Extraction
- Data mining is sorting through data to identify patterns and establish relationships.
Data Monetization and Data Science
- Familiarity with data monetization strategies and techniques, such as data commercialization, data marketplaces, and data value realization.
Natural Language Processing
- Proficiency in analyzing and extracting insights from unstructured text data, including sentiment analysis, topic modeling, and language understanding.
Problem-Solving and Analytical Thinking
- Strong problem-solving skills to identify architectural challenges, analyze requirements, evaluate options, and propose effective solutions.
Reporting and Dashboarding
- The ability to access information from databases, forms, and other sources, and prepare reports according to requirements.
Statistical Analysis
- Statistical analysis is used in support of decision-making and includes fundamental principles such as data collection and sampling.
#J-18808-Ljbffr