Data Science Lead, Prove
$179-200k
Plus variable commission / company bonus + Equity
More information about location
Identity verification platform
Job no longer available
Identity verification platform
201-500 employees
Job no longer available
$179-200k
Plus variable commission / company bonus + Equity
More information about location
201-500 employees
Company mission
To enable a digital world where every consumer and company can transact with trust.
Role
Who you are
- 6+ years in Data Science/Data Engineering, with at least 2 years in a technical leadership or architectural role
- Python, R, SQL, Cloud Platforms (AWS/GCP/Azure), Big Data tech (Spark, Kafka), Orchestration (Airflow), and MLOps tools
- Deep understanding of data modeling, schema design (SQL/NoSQL), statistical evaluation, and MLOps deployment patterns, especially in R&D functions that bridge research with production
- Exceptional ability to translate complex technical architectures into strategic business value for non-technical stakeholders
- If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles
What the job involves
- Reports To: Director, Data Science
- Department: Business Operations
- The Data Science Lead will serve as the strategic architect and research pioneer for the organization’s data ecosystem. This role is responsible for designing robust data architectures, leading research and development (R&D) for novel data sources, establishing rigorous analytical methodologies, and ensuring the seamless, scalable ingestion of high-quality data into downstream production solutions
- Blueprint Design: Design and oversee the evolution of scalable data architectures that support advanced analytics, machine learning (ML) modeling, and real-time processing
- Exploratory Research: Scout, evaluate, and pressure-test new internal, external, and alternative data sources (e.g., synthetic data, IoT streams, third-party APIs) for predictive power and commercial viability. Lead the ideation and feature engineering for these data sources and document how it aligns to current and future data architecture designs
- Proof of Concepts (PoCs): Lead rapid prototyping and PoCs to validate new technologies, algorithms, and data structures before scaling them to production
- Vendor & Partner Assessment: Technical vetting of data vendors and partners to ensure data quality, density, and seamless integration capabilities
- Framework Standardization: Define and document the organization's gold-standard methodologies for statistical analysis, experimental design (A/B testing), and ML modeling
- Evaluation Metrics: Establish rigorous validation protocols and evaluation metrics (e.g., precision/recall, drift detection, bias/fairness audits) to ensure model and data integrity
- Continuous Improvement: Keep the organization at the cutting edge of data science by translating academic research and emerging industry trends into practical business methodologies
- Productionalization Bridge: Serve as the critical bridge between R&D and Production, ensuring that complex analytical models and data sources are seamlessly ingested into core business products and solutions
- API & Interface Design: Oversee data delivery contracts between the DS ecosystem and downstream software applications to ensure the creation of clean, well-documented APIs
- Key Deliverables (First 12 Months):
- Data Source Playbook: A formalized framework for scoring, vetting, and onboarding new data assets
- Methodology Registry: A centralized repository of approved statistical models, evaluation metrics, and ingestion protocols to ensure team-wide consistency
- Feature Importance Registry & Feature Engineering Roadmap: a centralized repository connecting current data sources to their product value and impact of removal and/or possible substitutes to the roadmap of how Prove can leverage the signals in new and differentiated ways
- Architectural Roadmap: A 12 month to 3-year vision aligning data science infrastructure with corporate scaling goals
Our take
Prove's identity-proving solutions allow businesses to enable their customers to verify their identities with just a phone. It is used by more than 1,000 global enterprises and 500 financial institutions across multiple industries.
With more and more activity taking place online and via mobile devices, Prove offers companies speed and security while processing transactions. The identity verification space is buoyant, with many other companies providing services. But despite this competition, Prove has grown to be a leading and award-winning platform.
Prove's phone-centric tokenisation and passive cryptographic solutions have had tremendous corporate momentum. The company has been named to Deloitte’s prestigious Technology Fast 500 list several times and is well set to further its hold on the market.
Freddie
Company Specialist at Welcome to the Jungle
Insights
17% employee growth in 12 months
Company
Funding (last 2 of 9 rounds)
Oct 2023
$40m
LATE VC
Jun 2020
$100m
LATE VC
Total funding: $252.1m
Company benefits
- 401k Match
- Parental Leave Policy
- Stock Options
- Health benefits
- Wellbeing reimbursement
- Work From Home Opportunities
- Bonus Scheme
- Generous Vacation Time
Company HQ
NoMad, New York, NY
Leadership
Rodger Desai
(Founder & CEO)Studied at Harvard Business School after working as an Engineer for Exxon Mobil, General Electric, and Accenture, as well as co-founding several venture-backed startups.
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