Toptal

• Identify, develop, and close opportunities with enterprise clients by helping them solve complex business challenges. • Develop tailored solutions that help clients accelerate strategic initiatives and achieve measurable business outcomes. • Build a targeted portfolio of accounts from scratch—identifying, prioritizing, and developing your own book of business. • Partner with Client Partners to deepen and expand strategic relationships over time. • Prospect, pitch, negotiate, and close new opportunities while also expanding existing relationships.

• Analyze data, build models, test hypotheses, find root causes, develop prototypes, forecast performance, create Tableau reports, and write SQL scripts; and extract insights from these data activities to inform marketing decisions. • Use descriptive (what happened) and diagnostic (why did it happen) analytics to develop specific, actionable recommendations for marketing leaders. • Define metrics that are independent, holistic, accurate, encourage the right behaviors, and are aligned with company strategy and objectives. • Measure and diagnose the performance of SEM, SEO, and Generative AI channels—analyzing spend efficiency, keyword and query performance, organic visibility and share of voice, funnel conversion, and lead value/ROAS—to guide budget allocation and channel strategy. • Map marketing processes and channel journeys to their corresponding data flows across acquisition, engagement, and revenue generation. • Proactively identify and surface opportunities to improve efficiency, conversion, revenue generation, client and talent experience, operations, communication, systems & tools, cash usage, etc. • Work closely with marketing stakeholders, data analysts, and business process owners to empower data-backed decision making, balancing and prioritizing competing requests across teams. • Leverage Generative AI tools (such as Claude, Gemini, and ChatGPT) to accelerate analysis, automate reporting workflows, and evaluate the growing impact of AI-driven search and referral channels on marketing performance. • Build and maintain marketing data infrastructure from lead acquisition to revenue generation, setting up and integrating Google Analytics, Google Search Console, and Google Ads as required.

• Analyze data, build models, test hypotheses, find root causes, develop prototypes, forecast performance, create Tableau reports, and write SQL scripts; and extract insights from these data activities to inform marketing decisions. • Use descriptive (what happened) and diagnostic (why did it happen) analytics to develop specific, actionable recommendations for marketing leaders. • Define metrics that are independent, holistic, accurate, encourage the right behaviors, and are aligned with company strategy and objectives. • Measure and diagnose the performance of SEM, SEO, and Generative AI channels—analyzing spend efficiency, keyword and query performance, organic visibility and share of voice, funnel conversion, and lead value/ROAS—to guide budget allocation and channel strategy. • Map marketing processes and channel journeys to their corresponding data flows across acquisition, engagement, and revenue generation. • Proactively identify and surface opportunities to improve efficiency, conversion, revenue generation, client and talent experience, operations, communication, systems & tools, cash usage, etc. • Work closely with marketing stakeholders, data analysts, and business process owners to empower data-backed decision making, balancing and prioritizing competing requests across teams. • Leverage Generative AI tools (such as Claude, Gemini, and ChatGPT) to accelerate analysis, automate reporting workflows, and evaluate the growing impact of AI-driven search and referral channels on marketing performance. • Build and maintain marketing data infrastructure from lead acquisition to revenue generation, setting up and integrating Google Analytics, Google Search Console, and Google Ads as required.

• Equip revenue-generating teams with knowledge, skills, tools, and processes to sell confidently and effectively. • Combine strategic thinking with operational excellence to design, execute, and continuously improve scalable enablement programs that drive measurable business outcomes. • Support Sales Enablement strategy across various organizations, ensuring teams are prepared for evolving products, go-to-market strategies, and customer needs. • Own end-to-end enablement programs from planning through execution and reinforcement. • Build comprehensive enablement plans with clear objectives, timelines, and success metrics. • Design and deliver engaging instructor-led, self-paced, and live training. • Develop playbooks, programs, learning paths, and reference materials. • Measure program effectiveness and continuously improve based on feedback and performance data.

• Equip revenue-generating teams with knowledge, skills, tools, and processes • Design, execute, and continuously improve scalable enablement programs • Partner with executive leadership to translate business priorities into scalable enablement initiatives • Lead rollout strategies for new products, GTM messaging, sales motions, tools, and operational processes • Develop enablement roadmaps aligned with company objectives and sales priorities • Identify enablement gaps through performance data, stakeholder feedback, and sales insights • Own end-to-end enablement programs from planning through execution and reinforcement • Build comprehensive enablement plans with clear objectives, timelines, and success metrics • Design and deliver engaging instructor-led, self-paced, and live training • Develop playbooks, programs, learning paths, and reference materials with Toptal’s LMS and other tools • Facilitate workshops, webinars, office hours, and reinforcement sessions • Measure program effectiveness through adoption, engagement, behavior change, and business impact • Collect qualitative and quantitative feedback from stakeholders and learners • Share program impact with leadership through clear reporting and recommendations • Build trusted relationships with Sales Leadership and cross-functional teams • Consult with stakeholders to understand business needs and recommend enablement solutions

• Own the vision, strategy, and P&L for the AI Services practice, establishing it as a differentiated, revenue-generating offering within our MSP portfolio. • Develop repeatable service offerings and delivery frameworks that apply AI to ITIL processes — including Incident Management, Problem Management, Change Enablement, Service Request, and Knowledge Management — across a diverse client base. • Define pricing models, packaging, and go-to-market strategy for AI-enabled ITSM services in collaboration with Sales and Marketing. • Build internal IP: playbooks, accelerators, and pre-configured AI assets on ServiceNow that reduce time-to-value for clients. • Serve as the executive-level AI advisor to key clients, engaging C-suite and IT leadership stakeholders to assess maturity, identify opportunities, and co-create AI-driven ITSM roadmaps. • Lead discovery workshops and maturity assessments to baseline clients’ current ITSM and AI capabilities. • Present business cases and ROI models for AI investments to client executives, translating technical capabilities into tangible outcomes (e.g., MTTR reduction, ticket deflection rates, cost avoidance). • Maintain trusted advisor relationships across a portfolio of accounts, ensuring client satisfaction and identifying expansion opportunities. • Oversee the architecture and delivery of ServiceNow AI solutions for clients: Now Assist, Virtual Agent, Predictive Intelligence, ITOM AIOps, NLU, and generative AI integrations. Govern integrations between ServiceNow and external AI platforms (e.g., Azure OpenAI, AWS Bedrock, Anthropic) to extend client capabilities. • Establish delivery standards and quality assurance processes to ensure consistent, best-practice implementation across all client engagements. • Drive adoption of AI-powered ServiceNow features that measurably reduce client operational burden and improve end-user experience. • Apply deep ITIL v4 expertise to ensure AI augments and elevates client service management processes rather than introducing risk or technical debt. • Champion a shift-left philosophy through AI-driven self-service, knowledge deflection, and automated resolution for clients. • Establish governance and measurement frameworks (KPIs, SLAs, OLAs) for AI-enhanced ITSM processes delivered to clients. • Recruit, develop, and lead a high-performing team of AI architects, ServiceNow practitioners, and ITSM consultants. • Establish career paths and capability-building programs to grow AI and ITSM expertise across the broader services organization. • Foster a culture of innovation and continuous improvement, encouraging the team to test and adopt emerging AI capabilities. • Manage and deepen the company’s relationship with ServiceNow as a partner, including ISV/reseller programs and co-sell opportunities. • Evaluate and manage relationships with complementary AI and AIOps vendors to enrich the client solutions portfolio. • Represent the company at industry events, conferences, and ServiceNow communities as a thought leader in AI-powered ITSM.

• Own the vision, strategy, and P&L for the AI Services practice, establishing it as a differentiated, revenue-generating offering within our MSP portfolio. • Develop repeatable service offerings and delivery frameworks that apply AI to ITIL processes — including Incident Management, Problem Management, Change Enablement, Service Request, and Knowledge Management — across a diverse client base. • Define pricing models, packaging, and go-to-market strategy for AI-enabled ITSM services in collaboration with Sales and Marketing. • Serve as the executive-level AI advisor to key clients, engaging C-suite and IT leadership stakeholders to assess maturity, identify opportunities, and co-create AI-driven ITSM roadmaps. • Maintain trusted advisor relationships across a portfolio of accounts, ensuring client satisfaction and identifying expansion opportunities. • Oversee the architecture and delivery of ServiceNow AI solutions for clients: Now Assist, Virtual Agent, Predictive Intelligence, ITOM AIOps, NLU, and generative AI integrations. • Establish delivery standards and quality assurance processes to ensure consistent, best-practice implementation across all client engagements. • Recruit, develop, and lead a high-performing team of AI architects, ServiceNow practitioners, and ITSM consultants.

• Connect and engage with prospective clients from inbound leads • Seek new business opportunities and develop relationships with potential customers • Guide clients throughout required sales stages • Manage the sales cycle from discovery through to close • Execute a customer-centric approach across all interactions • Research clients and stay updated on industry trends • Collaborate with team to respond to inbound client inquiries • Participate in 1-1 sales training and complete personalized training program • Mentor new team members and contribute to team success

• Advance research on agentic AI systems trained on real-world interaction signals and multimodal data. • Design and experiment with learning paradigms for large-scale models, including RAG, supervised fine-tuning, RLHF, DPO, and GRPO-style methods. • Develop multimodal representation learning approaches, including joint embedding spaces across text, audio, logs, and structured interaction traces. • Improve speech and audio intelligence capabilities, including STT, ASR, and audio-driven learning signals. • Research methods for enhancing agent reasoning, planning, tool use, and adaptation in real-world environments. • Define how complex behavioral and interaction signals can be translated into effective training objectives for large-scale models. • Build and refine evaluation methodologies for agent performance in real-world, domain-specific scenarios. • Collaborate with engineering and product teams to bring research ideas into production systems. • Identify patterns in real-world workflows and convert them into generalizable modeling and representation strategies. • Contribute to the long-term research direction of Toptal’s agentic AI systems and multimodal capabilities. • Stay current with academic and industry research and integrate relevant advancements into internal systems.

Role Description We are looking for a Senior Data Scientist to join us as the first Data Scientist on a new product we are building. This is a founding role: you will shape the data science function from the ground up, set technical direction, and own the end-to-end delivery of intelligent systems that define how our product creates value. You will tackle open-ended problems involving: - Task Mining - Process Mining - Behavioral workflow analysis - Pattern discovery - Predictive modeling - Applied GenAI/ML systems The goal is not just to build models, but to turn raw interaction data into measurable product and business impact: discovered workflows, bottlenecks, optimization opportunities, and scalable foundations for future DS/ML work. This is a remote position. We do not offer visa sponsorship or assistance. Resumes and communication must be submitted in English. Qualifications - 5+ years of professional experience in Data Science, Machine Learning, or Applied ML roles. - Demonstrated experience operating as the sole or lead Data Scientist on a product or team — owning problems end-to-end without senior DS supervision. - Strong experience with supervised and unsupervised ML, modern ML/data tooling, and the judgment to select the right approach for the problem. - Practical familiarity with representation learning, sequence modeling, Transformers, LLMs, or GenAI systems where relevant to product use cases. - Experience handling large-scale structured, unstructured, event, or interaction datasets. - Advanced proficiency in Python and SQL, with hands-on experience using tools such as PyTorch, scikit-learn, pandas/Polars, experiment tracking, and production ML workflows. - Experience deploying ML models, data pipelines, or intelligent systems into production. - Familiarity with Task Mining, Process Mining, event-log analysis, behavioral analytics, workflow automation, or adjacent domains. - Advanced degree in Computer Science, Data Science, AI, Statistics, Mathematics, or a related field is a plus; equivalent practical experience is strongly valued. Requirements - A founder’s mindset: full responsibility for outcomes, not just deliverables. - Comfort operating in high ambiguity: able to turn unclear product goals, noisy data, and incomplete requirements into an executable roadmap. - Strong business sense — connects technical work to commercial impact and measurable product value. - Pragmatic technical judgment — knows when to use advanced ML, when to simplify, and when better data, labeling, or evaluation is the real bottleneck. - Ability to build foundations for rapid scaling: reusable datasets, pipelines, metrics, evaluation frameworks, and modeling patterns future DS/ML hires can build on. - Highly proactive problem solver who acts without waiting for detailed instructions. - Excellent communication skills, with the confidence to push back constructively and propose direction. Nice to Have - Previous experience as a first or early Data Scientist at a startup or new product line. - Direct experience with Task Mining, Process Mining, workflow intelligence, RPA, or productivity analytics. - Experience with LLMs and Generative AI applications, especially evaluation, structured outputs, semantic labeling, summarization, or human-in-the-loop workflows. - Experience working with privacy-sensitive behavioral, productivity, or user-interaction data. - Experience with product experimentation, causal inference, or measuring the impact of workflow/process interventions. - Knowledge of MLOps and distributed processing frameworks, such as Spark. - Experience with cloud environments, especially GCP.