Data Science Analyst - integrated resources : Job Details

Title: Data Science Analyst Location: Houston TX - Hybrid (4 Days Onsite and One day Remote) Contract: 6 Months and Possibility of ExtensionPosition Summary: • Under general supervision, the Technical Analyst will bring a strong analytical mindset in support of business needs analysis and data/analytical solution development. This role combines technical capabilities with business analysis to analyze, test, and implement solutions that drive operational efficiency through advanced analytical capabilities. The ideal candidate will have a strong technical background and be comfortable working with large datasets (spatial and temporal) and collaborating with cross-functional teams including data scientists to deliver impactful outcomes. Strong analytical thinking, self-drive, and excellent communication and collaboration skills are essential. Duties and Responsibilities: • Analyze business processes and translate requirements into technical/analytical specifications. • Design and develop scripts, APIs, and automation tools to support advanced technical analysis. • Build and maintain data pipelines in support of data analytics. • Collaborate with stakeholders and data scientists to define problems, document solutions, and support implementation. • Develop/improve reports and visualizations as needed to communicate insights and metrics. • Ensure data quality and reliability in support of analytics and insights. • Support Agile development processes including sprint planning, backlog grooming, and UAT. • Prepare technical documentation and contribute to knowledge sharing across teams. • Apply geospatial analysis techniques and tools to support location-based decision-making. Qualifications: • Bachelor's or Master's degree in computer science, Data Science, or related field. • 3-5 years of experience in a hybrid technical/business analyst role. Technical Skills Required: • Programming & Scripting: Python, Java, SQL, R • Databases & Analytics: Snowflake, PostgreSQL, MongoDB, DataStax/Astra DB, Data modeling, ETL • Cloud & DevOps: AWS (S3, SageMaker), • Tools & Frameworks: Git, Jira, Confluence, PyCharm, Notebooks • Machine Learning and Deep Learning: Pandas, NumPy, Scikit-Learn, OpenCV, PyTorch, Tensorflow, OpenCV • GenAI/LLMs: Hands-on experience with generative AI tools and frameworks • Geospatial Tools: Experience with GIS platforms such as ArcGIS, QGIS, CARTO or geospatial libraries in Python Knowledge, Skills and Abilities: • Strong analytical and problem-solving skills. • Ability to work with large-scale datasets and perform advanced data mining. • Excellent communication and stakeholder engagement skills. • Self-driven, collaborative, and customer-focused mindset. • Experience in Agile environments and cross-functional teams.