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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist IV - **Company:** TEKSYSTEMS INC. - **Location:** Menlo Park, CA, United States (Remote available) - **Salary:** $166,400.0 - $187,200.0 - **Contract:** Temporary contract - **Skills:** Data Analysis, Big Data, Document-Oriented Databases, Inventory Management Software, Python (Programming Language), Machine Learning, Operational Data Store, Raw Data, Power BI, SQL Databases, Tableau (Software), Data Processing, Pandas, Tools for Reporting - **Published:** October 7, 2026 - **Apply:** https://dejobs.org/x/x/05EAF50545134107B839D03BD1573152/job/ ## About the Role * Solid, practical SQL used daily, with proficiency working independently from raw data to a finished answer. * Experience writing performance-aware SQL against large-scale data warehouses, including joins and window functions. * Strong Python skills for analysis, data wrangling, and light automation, using libraries such as pandas or equivalent. * Hands-on experience designing, building, shipping, and maintaining dashboards and self-serve reporting that partners adopt and use regularly. * Working statistical knowledge for operational analytics, including descriptive statistics, trend and anomaly reasoning, and sound sampling and significance judgment. * Demonstrated ability to establish baseline metrics, data quality checks, and reporting hygiene in previously under-supported domains. * Strong partner communication skills, including managing an inbound request queue, clarifying vague asks, setting expectations, and closing the loop effectively. * Proven ability to work as a generalist across multiple domains, ramping quickly without a fully-formed playbook and delivering value in unfamiliar areas. * Prior experience supporting technical or engineering stakeholders, such as data engineers, data scientists, infrastructure teams, or platform engineering teams. * Comfort operating in AI-assisted development environments and using AI tooling as part of the daily analytics workflow. * Ability to collaborate closely with data engineers on data models and pipelines, identifying gaps and influencing design to meet analytics needs. * Applied statistics skills focused on operational analytics, with an understanding that deep machine learning is not required for this role. Additional Skills and Qualifications * Hands-on experience with a modern BI or dashboarding stack such as Tableau, Power BI, or similar tools. * Familiarity with infrastructure and operational data domains, including asset and inventory data, network telemetry, endpoint or client platform telemetry. * Experience building self-service analytics solutions that become a trusted source of truth for technical and business partners. * Background working within production engineering, infrastructure, or platform organizations is a plus. * Ability to document data products, dashboards, and metrics clearly so technical audiences can understand and trust the outputs. * Comfort working with engineering-focused audiences who ask precise questions and review queries and logic in detail. * Strong judgment, reliability, and ability to work safely and respectfully with others while safeguarding business operations and reputation., * SQL, Python, Analytics, Data Science, Tableau, Power BI, Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors. ## Description This fully remote Data Scientist role focuses on infrastructure and operations analytics across multiple technical domains. You will serve as the primary analytics partner for engineering and platform teams, building data products, dashboards, and reporting frameworks that make complex infrastructure data usable and reliable. The work is broad, hands-on, and customer-facing, with a strong emphasis on practical SQL and Python, operational statistics, and close collaboration with technical stakeholders to improve visibility, decision-making, and reporting hygiene in areas that have had little or no data science coverage., * Own day-to-day analytics for horizontal infrastructure operations, including intake, scoping, and turning around analysis requests from partner teams. * Work end-to-end from raw data to finished, trustworthy answers using SQL and Python, ensuring outputs are clear, accurate, and actionable. * Build, ship, and maintain dashboards and self-serve reporting so recurring questions become self-service instead of one-off requests. * Design reporting that engineering partners actually adopt, iterating based on feedback to maximize usability and impact. * Support operational areas such as asset inventory, network-side systems, and client platform and endpoint services with robust analytics and reporting. * Provide the analytical layer for infrastructure data products and services, including shared interfaces and tooling that make infrastructure data usable across the organization. * Establish baseline metrics, data quality checks, and reporting hygiene in domains that previously had no dedicated data science support. * Partner closely with data engineers on data models and pipelines, flagging gaps, shaping schema design, and influencing what gets built to support analytics needs. * Manage an inbound request queue from technical partners, clarify vague or ambiguous asks, set expectations, and close the loop with clear communication and documentation. * Apply working statistical knowledge to operational analytics, including descriptive statistics, trend and anomaly detection, and sound sampling and significance judgment. * Operate comfortably in AI-assisted development environments, using AI tooling as part of the daily analytics workflow for analysis, data wrangling, and light automation. * Collaborate with data engineers, data scientists, and infrastructure and platform engineering teams who consume infrastructure data products and rely on reliable, well-documented data. * Provide operational visibility and trusted reporting to team leadership to support informed decision-making and oversight of infrastructure and platform performance. * Adapt quickly to unfamiliar domains and projects without a fully-formed playbook, bringing generalist range to support diverse infrastructure operations areas. * Maintain clear documentation of data sources, dashboards, metrics definitions, and analytical methodologies to ensure transparency and reusability across the organization., * This role is 100% remote within the United States, providing flexibility in where you work while supporting teams based in Menlo Park, California. You will operate in a production engineering and infrastructure context that builds and runs internal platforms and services, including asset inventory systems, network-side platforms, and client endpoint services. The environment is highly technical and engineering-focused, with partners who ask precise questions and engage directly with your queries, dashboards, and data products. You will work primarily with large-scale data warehouses, modern BI and dashboarding tools such as Tableau or Power BI, and Python-based analytics workflows, including AI-assisted development tools. The team emphasizes reliable, well-documented data, operational visibility, and scalable self-service reporting, with 15 days of PTO accrued annually to support work-life balance.