Data Analyst

International SOS•San Antonio, TX

29d

About The Position

At International SOS, we are in the business of protecting and saving lives. For 40 years, we have delivered customised security risk management, health, and wellbeing solutions to organisations worldwide. With a presence in 90 countries and a team of nearly 13,000 experts, we provide 24/7 support to help organisations fulfil their Duty of Care responsibilities. Now, we’re looking for talented individuals to join our team and make a difference. The Data Analyst is responsible for creating & providing correct, accurate & complete data, reporting, modeling, presentation & analysis that support business objectives. The candidate will provide effective recommended solutions in data sets, converting insights into strategic solutions & options that lead to & support high-quality, data-driven decision making. This role requires an understanding of statistical methodologies, data visualization techniques, and the ability to translate analytical findings into actionable business recommendations.

Requirements

Data modeling and analysis experience.
Data visualization and presentation skills.
Strong knowledge of relational database concepts and structures.
Demonstrable knowledge of MS SQL Server.
Knowledge of DAX, T-SQL, C#, D3, R or Python or any other statistical programming language for advanced analyses and predictive analytics.
Ability to write stored procedures, functions & reporting.
Develop dashboards, data models in Power BI.
Experience working & creating databases, dashboards, reporting using relevant data leading to data driven decision making.
Problem solving, quantitative, qualitative & analytical skills.
Effective communication, collaboration skills.
Experienced using SQL with the ability to perform effective querying involving multiple tables and subqueries.
Working knowledge of Data Mining Principles, Predictive Analytics, Mapping, Collecting Data from Multiple Systems including but not limited to cloud-based data sources.
Ability to extract data, format & present data customizing the data including written & verbal communication to your audience.
Apply data quality standards, ensuring consistency and reliability of data across various platforms.
Experienced using analytics techniques that report correct, accurate & complete information, achieve timelines, including causing a positive impact on the brand of the organization.
Excellent communication and interpersonal skills, with the ability to engage with stakeholders at all levels of the organization.
Collaborate with business leaders to understand their analytical needs and deliver insights that drive strategic decision-making.
Present findings and recommendations to both technical and non-technical stakeholders in a clear and concise manner.
Technical Knowledge across a broad range of digital & data technologies.
AI Powered Business Intelligence: Strong ability to analyze data, generate insights & automate decision making using AI platforms. Example but not limited to Power BI Premium-Copilot, Tableau - Einstein, Looker - Google, Qlik - Sence.
Machine Learning AI: Ability to implement & maintain advanced analytics machine learning platforms. Example: Databricks, Google Vertex, AWS, Azure.
AI Data Structure: Strong ability to organize end to end data architecture for AI / ML use cases, aligning data architecture with the business AI strategy including designing a scalable, reusable AI data platform.
AI Data Pipeline and Integration: Ability to assist in designing and overseeing data ingestion pipelines. Integrate structured, semi structured and unstructured data sets, ensure reliable data flow & cause real time AI self-service tools to provide correct, accurate and complete information.
AI Data Modeling: Design and build data models optimized for AI analytics and ADHOC reporting, governing feature stores and support time-series, graphs, embedded based models.
AI Quality Governance: Ability to define data quality governance, implementing validation, lineage and meta data management including governing labeling within production and process’s data.
AI Security, Privacy & AI Responsibility: Strong ability to implement controls specific to data, ensuring compliance, including mitigating bias through data design and governance.
Minimum of 2 to 5 years of professional experience in data analytics or a related field.
Proficient in AI Business Intelligence, Machine Learning, Data Architecture, Data Pipeline / integration, Data Medeling, Governance and Security / Controls.
Proficient in statistical analysis, data modeling, and machine learning techniques.
High level of proficiency in data visualization within Power BI Premium.
Proficiency in programming languages SQL, Python, R.
Effective communication and interpersonal skills with the ability to convey complex findings to both technical and non-technical audiences.
Proactive forward thinker focused on delivering exceptional results.
Bachelor's or Master's degree in a relevant field (e.g., Data Science, Statistics, Computer Science).
Certifications in relevant; tools, technologies, and best practices.
Background Check & Screening: Ability to pass required background checks and clearance procedures, demonstrating the trustworthiness and eligibility for handling sensitive information.
Excellent level of English, written and spoken.

Nice To Haves

Additional languages a plus.

Responsibilities

Ability to problem solve complex reporting scenarios.
Proactive in causing the Data Analytics Team in achieving timelines for submissions of CDRL’s, ADHOC reporting’s, Invoicing data.
Creates, documents, & maintains analytical Dashboards in alignment with contractual requirements.
Applies quality controls and departmental standards to ensure quality standards, organizational expectations, and audit requirements are achieved.
Ensure accuracy of data & deliverables of Analytics Team deliverables applying comprehensive controls, policies and processes with attention to all technical aspects.
Develop & maintain data models, reporting systems, data automation systems, dashboards and performance metrics support that support key business decisions.
Analyzes business functions & key operations performance metrics.
Utilizes advanced data modeling, predictive modeling and analytical techniques to interpret key findings from company data and leverage these insights into initiatives that will support business outcomes.
Examine, interprets & reports results of analytical initiatives to stakeholders customizing your written & verbal communication to your audience.
Optimizes processes for data intake, validation, mining & engineering as well as modeling, visualization, and communication deliverables.
In collaboration with leadership, champion & cause One Team Culture to come to life within the team.
Develops and managing business intelligence solutions (MS SQL Server Reporting Services (SSRS) and Power BI) for the organization.
Providing SSRS and Power BI Tools, reports, but not limited.
Identifies improvement opportunities within operations to aid in driving efficiencies and profitability.
Collaborating with team members for the purpose of collecting data and producing exception reports to cleanse data at the origin.
Analyzing business requirements and processes and recommending them to the management and executives for implementation.
Creates and maintains documentation that includes the design, requirements and user manuals for the organization & SOPs.
Writes stored procedures to process the data.
Supports the delivery of reporting contract deliverables to the Client.
AI Tools for Data Analysis: Ability to build and apply AI-powered tools (like automated analytics, forecasting, or pattern detection) to analyze large data sets including use machine learning features in tools, Python, spreadsheets, & BI platforms.
Data Preparation for AI Modeling: Ability to clean, organize, & label data to enable it to be utilized effectively within AI systems, including identifying missing, incorrect, or biased data that could AI results.
Interpreting AI Outputs: Ability to understand & explain results produced by AI models (predictions, classifications & trends) including translate complex AI findings into clear insights.
AI Automation: Apply, build & automate dashboards, reports and alters, identify where AI can save time & improve decision making.