Senior analyst data
At Forrester, we’re trusted to work on trailblazing, mission critical problems that business and technology leaders face today. That’s why we’re always looking to empower talented individuals to perform at their best every single day. We’re proud of our community of smart people and vibrant voices who come together to do what’s right by our clients and each other. Our success is driven by curiosity, courage and customer obsession. The confidence and drive to be bold at work. Join us and build an extraordinary future.
About This Role: Forrester Research is seeking a Senior Analyst to be a critical member of the research team writing for our data, AI, and analytics body of work. This work serves data and AI leaders and helps them achieve high performance — the ability to deliver great business results through data, AI, and technology. It also guides vendors in defining the future of the market. The Senior Analyst will do work that encompasses: 1) designing processes to manage the full data lifecycle including, data ingestion and pipelines, processing and transformation, integration, risk management, data products including semantics and data models, dataOps and storage and retention — to deliver AI solutions and applications; 2) understanding the role of different data types underlying AI solutions, including unstructured text, document, image, and video data, streaming data, geospatial data, and graph data; and 3) fostering a culture of collaboration across our research, sales, product, and customer success teams. The Senior Analyst has a strong understanding of practitioner-level data leaders and helps them understand the implications of data and technology to build a solid data foundation for the AI enterprise. Job Description: The Senior Analyst will work as part of a high-performing team with a strong emphasis on collaborating with others in all aspects of the job. The Senior Analyst is expected to:- Conduct primary research on: 1) The full lifecycle of data in the enterprise, particularly as it relates to the development of AI solutions and applications; 2) data engineering and the process of transforming raw data for analytical and operational use cases; 3) modern data management practices and solutions, including evaluation of vendors offering commercial solutions for enterprise; 4) DataOps, including best practices and trends for handling massive amounts of enterprise data in production; and 5) deep understanding of data requirements for training and grounding predictive and generative AI applications. This research will help clients navigate challenges by providing insights on data needs, investment prioritization, cost optimization, and long-term development strategy.
- Create approximately eight to 12 high-quality, actionable, analytically deep, and fact-based research projects per year which include a mixture of written reports, tools, webinars, videos, blogs, podcasts, infographics, and other intellectual property. Work alongside sales and marketing teams to promote visibility for this research.
- Drive and lead key Forrester Wave™ and Landscape reports.
- Consult with clients to apply Forrester’s research in the context of their specific business environment and help solve their problems through inquiry, guidance, and advisory and consulting engagements.
- Present at Forrester-sponsored and industry-related events, as well as deliver client webinars.
- Establish an industry presence as an influential speaker and thinker, build relationships with journalists who cover the sector, and participate in press inquiries as necessary.
- Support business development and prospect conversations as arranged by Forrester’s account leadership teams.
- Fosters a style that drives a culture of cross-team collaboration, mentorship, integrity, and relentless and positive pursuits.
- A BA/BS degree.
- Five or more years of experience in a data management, data engineering, data architecture, or data science role working hands-on with developing data platforms, data pipelines, data products, and/or AI and analytical outputs.
- Demonstrated expertise in at least one of the following markets: data catalogs, data pipelines, data platforms, data governance solutions, and analytics and AI/ML solutions. Knowledge of vendors, key features and capabilities, and use cases.
- A demonstrated ability to serve as an advisor to senior leaders and C-level clients.
- Superior client-facing communication, listening, critical thinking, and collaboration skills with researchers, subject-matter experts, and client leaders.
- Strong knowledge of the issues and challenges that data and AI executives and leaders face, and expertise in the broad implications of current and emerging technology markets, economics, labor, and econometrics.
- The ability to take complex, disparate ideas and distill them into simple, provocative concepts; a willingness to take a stand on outcomes with clients, vendors, press, and competition.
- The ability to travel 30% of the time.
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