Technical Analyst-Data Science

Job Title: Technical Analyst-Data Science
Job Location: Houston, TX  (Hybrid 4 days a week in office)
Job Duration: 6-7 Months (possibility of extension)

Job 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.