Data Scientist V-6355

itD Tech•San Jose, CA

3d•Hybrid

About The Position

itD is seeking a Data Scientist V to drive data-informed decision-making by translating large-scale datasets into actionable insights, defining business objectives and success metrics, and developing analytical models that identify trends, uncover opportunities, and guide strategic decisions. The role is a six-month contract with potential for extension, based in a hybrid arrangement in Menlo Park, California, with onsite work three days per week. The pay rate is up to $60 per hour, depending on experience. Applicants must be direct W2 candidates; sponsorship is unavailable. The Data Scientist will conduct exploratory analyses, develop and optimize SQL workflows, build and evaluate predictive and forecasting models, create dashboards and visualizations, and communicate findings and recommendations to technical and non-technical audiences. The role also includes defining measurable objectives and key results with stakeholders, developing research plans and experiments, and contributing to itD’s internal practice community through meetings, thought leadership, case studies, learning materials, networking, and Digital Transformation practice materials. itD describes itself as a woman- and minority-led consulting and software development company with a global community and a culture emphasizing diversity, innovation, integrity, empowerment, and strong business results. Employees may work with Fortune 500 companies and high-performance teams across industries. The company offers medical, dental, vision, and life insurance; paid holidays; a 401(k) with matching; and networking, career learning, and development programs. itD provides equal opportunity and reasonable accommodation to applicants and employees with disabilities.

Requirements

10 or more years of industry experience solving analytical problems using quantitative methods and data-driven approaches.
Advanced SQL proficiency, including complex queries, joins, aggregations, filtering, grouping, and analytical functions.
Python proficiency for data analysis, scripting, and analytical problem-solving.
Experience conducting exploratory data analysis, defining and monitoring key metrics, investigating metric changes, and identifying business opportunities.
Strong understanding of statistical analysis, quantitative methods, and data interpretation.
Experience collaborating with stakeholders to define business objectives, OKRs, and measurable success metrics.
Ability to independently analyze complex datasets and develop actionable, evidence-based recommendations.
Strong communication skills, including the ability to explain analytical approaches and present complex findings to technical and non-technical audiences.
Bachelor’s degree in a relevant field or equivalent work experience.
Must be a direct W2 candidate; sponsorship is not available.

Nice To Haves

Experience designing interactive dashboards, data visualizations, and high-performance analytical reports.
Experience developing predictive and forecasting models using regression, clustering, classification, or other statistical techniques.
Experience designing research plans, formulating hypotheses, and conducting experiments to evaluate business questions.
Demonstrated ability to develop compelling data narratives that translate analytical findings into prioritized business actions.
Experience working with large-scale data environments and supporting data-driven decisions in complex organizations.

Responsibilities

Conduct exploratory data analysis on large-scale datasets to identify trends, patterns, correlations, root causes of metric changes, and business improvement opportunities.
Partner with stakeholders to define business objectives and success metrics, establish measurable objectives and key results (OKRs), and track short- and long-term progress.
Develop and optimize advanced SQL queries and analytical workflows to extract, transform, analyze, and interpret complex datasets.
Build and evaluate predictive and forecasting models using statistical and machine learning techniques, including regression, clustering, and classification, and provide actionable recommendations.
Design high-performance dashboards and visualizations that communicate key metrics, present clear narratives, and help stakeholders explore data and monitor performance.
Present analytical findings, prioritized recommendations, and estimated business impact to technical and non-technical audiences.
Develop research plans, formulate hypotheses, select analytical methods, and conduct experiments to answer business questions and identify opportunities.
Attend regular internal practice community meetings.
Collaborate with the itD practice team on industry thought leadership.
Complete client case studies and learning materials, including blogs and media content.
Build materials that contribute to the Digital Transformation practice.
Attend internal itD networking events, in person and virtually.
Work with leadership on career fast-track opportunities.