Architect, Data Science
$145,000 - $200,000 per year
ApplyArchitect, Data Science
Posted yesterday
SENIORITY
Senior
SALARY
$145,000 - $200,000 per year
About the role
- Define clear business-value metrics (e.g., ROI, revenue impact, cost reduction) alongside technical performance targets for every engagement.
- Lead technical scoping, feasibility assessments and solution design for proposals, Statements of Work and client pitches.
- Design scalable, secure and maintainable end-to-end multi-layer ML/AI pipelines, spanning data analysis, feature engineering, model training, deployment and MLOps.
- Direct cross-functional delivery teams of Data Scientists, Data Engineers and ML Engineers to execute solutions aligned with architectural standards.
- Establish code quality standards, model validation protocols and technical best practices to prevent technical debt and ensure system reliability.
- Articulate technical concepts, model trade-offs and operational risks clearly to both technical teams and non-technical C-suite stakeholders.
- Design operational workflows and user integration strategies to drive high adoption of AI/ML tools among end-users.
- Conduct client enablement workshops and knowledge transfer sessions to build internal capability and ensure long-term solution sustainability.
- Our Ideal Candidate's Skills and Experiences:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, economics or a related field.7+ years of experience in data science & AI/ML, including large-scale solution deployments.5+ years in a client facing role, preferably in a professional services firm.
- Strong communication skills with the ability to influence technical and executive stakeholders.
- Proven track record designing and implementing modern data science solutions in at least two of the following areas: forecasting, anomaly detection, recommendation system, computer vision, risk modeling or mathematical optimization.
- Expert knowledge of Python, SQL and strong hands-on experience with Databricks (Unity Catalog, MLFlow, Delta Tables, etc.).Proficiency with commercial and open-source LLM APIs and tooling like Hugging Face, LangChain, DSPY etc, as well as coding assistants.
- Experience with rapid prototyping and creating proofs of concept, technical presales presentations and pricing for engagements.
- Prior experience with revenue management, price modeling and causal Inference.
- What We Promise You:
- Meaningful, cutting-edge projects in Data Science & AI/ML domain with clients across industries, from Fortune 500 firms to disruptive startups.
- Rapid learning and mentorship opportunities with Data & AI thought leaders and practitioners.
- A culture of experimentation, innovation and continuous improvement.
- Opportunity to be a conference speaker, blogger and writer.
- A diverse and inclusive team with collaborative culture, where your voice and ideas are heard.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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