Senior Analyst, Data, Analytics and Machine Learning

Responsibilities

• Conduct and deliver primary research:
  Ensure that a modern data foundation that includes data quality, governance and context‑ready data amplifies development of analytics, data science, ML, and AI internal products.
• Help clients activate, measure, and scale the use of analytics, data science, ML, and AI for business‑focused outcomes and use cases.
• Drive alignment among internal stakeholders on data and analytical priorities that support business impact.
• Create approximately eight to twelve 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, which are deep, objective evaluations of the most important vendors of data, analytics, and AI technologies.
• Consult clients to apply Forrester’s research in the context of their specific business environment and help solve their problems through short‑term and longer‑term consultative 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.
• Foster a style that drives a culture of cross‑team collaboration, mentorship, integrity, and relentless and positive pursuits.

• A strong academic record: BA or BS degree as a minimum; MBA or MS in a related field is preferred.
• At least five years’ hands‑on experience in data science, machine learning models, data engineering, data management, and/or related disciplines in a $1 billion enterprise or with a technology vendor.
• Understanding of the market for data science/ML and data management technology, including vendor capabilities, top use cases, common architectural patterns, and barriers to implementation and adoption.
• A demonstrated ability to serve as an advisor to senior management 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 AI and technology executives face; 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, bold concepts; a willingness to take a stand on outcomes with clients, vendors, press, and competition.
• The ability to travel 30% of the time.

Demonstrates expertise in data science, machine learning, and data management, with a strong ability to communicate complex ideas effectively to senior management and clients. Proven track record in conducting high‑quality research and delivering actionable insights that drive business outcomes.