Lead Data Scientist - Go-to-Market & Analytics (NY/Hybrid or Remote)

Alexander Group•New York, NY

1d•$230,000 - $250,000•Hybrid

About The Position

Lead Data Scientist – Go-to-Market Strategy & Analytics Alexander Group: The Go-to-Market Consulting Leaders Alexander Group provides go-to-market consulting services to marketing, sales, service and talent leaders. With over 40 years of developing practical, executable solutions, we are singularly focused on helping commercial teams unlock their full potential and reach new revenue goals. With a robust network of offices, Alexander Group maximizes growth opportunities for our clients around the globe. Founded in 1985, we’ve served more than 3,000 companies around the world, across all industries. This experience gives us not only a highly sophisticated set of best practices to design go-to-market strategy—we also have a rich repository of industry data that informs all of our recommendations. Our dedication to sales strategy and revenue growth has led to: More than 70% of our clients being Fortune 500 corporations Project work in more than 25 countries Extensive industry experience in B2B markets Position Overview: We are seeking a Lead Data Scientist to lead our data science practice and drive innovation at the intersection of advanced analytics, machine learning and GTM strategy. This role combines technical leadership, client delivery and business development support, making it ideal for someone who thrives in both hands-on modeling and strategic advisory environments. This role is designed as a senior, hands-on “player-coach” position with a clear growth path into broader practice leadership. As the data science team and offerings continue to scale, the Lead Data Scientist will have the opportunity to evolve into a Director of Data Science role, taking on increased responsibility for practice strategy, roadmap and executive-level engagement based on demonstrated impact and leadership. The Lead Data Scientist will oversee a team of data scientists, guide the evolution of our analytical methodologies, and ensure high-quality delivery across client engagements. This individual will also play a key role in shaping new data-driven offerings and supporting client pursuits as a technical expert and solution architect.

Requirements

Candidates MUST BE fully authorized to work in the U.S. without current or future need or potential need for visa sponsorship
5–10+ years of experience in data science, analytics or applied machine learning roles
Proven experience leading teams and managing complex analytical projects
Strong proficiency in Python (pandas, scikit-learn, etc.) and SQL; familiarity with R
Experience building and deploying predictive models in business contexts
Strong familiarity with RevOps, sales or GTM data (e.g., CRM, pipeline, account-level data)
Ability to connect data science work to business outcomes, particularly in B2B environments
Strong communication skills with the ability to explain technical concepts to non-technical stakeholders
Experience in Consulting, Private Equity or enterprise B2B environments is highly preferred

Nice To Haves

Experience working with cloud platforms and modern data infrastructure, including AWS, Azure or GCP, as well as warehouse/lakehouse platforms such as Snowflake and Databricks a plus
Exposure to production ML systems (MLOps, model deployment, monitoring) a plus
Experience building internal data products or client-facing analytical tools (e.g., dashboards, apps or reusable platforms) a plus
Experience with NLP, LLMs or AI-driven applications a plus

Responsibilities

Team Leadership & Practice Development
Lead, mentor and grow a team of 7–10 data scientists, fostering a high-performance and collaborative culture
Establish best practices for modeling, code quality and reproducibility across engagements
Drive the development of new analytical frameworks, tools and reusable assets
Client Delivery & Technical Oversight
Oversee end-to-end data science workstreams across multiple client engagements
Ensure rigor, scalability and business relevance of all models and analyses
Translate complex analytical outputs into clear, actionable insights for executive stakeholders
Modeling & Methodology Innovation
Own and evolve core methodologies across areas such as customer targeting, segmentation, cross-sell, churn prevention, forecasting/quota optimization and marketing performance optimization
Develop and apply machine learning models (e.g., unsupervised and supervised learning, time series, NLP-based approaches) to solve GTM challenges
Explore and integrate emerging AI capabilities (e.g., LLMs, automation, augmentation tools) into client solutions and internal workflows
Business Development & Client Engagement
Partner with consulting leaders to support business development efforts as a technical expert
Participate in client meetings, proposals and solution design as a “secondary seller”
Translate client needs into scalable analytical approaches and differentiated offerings