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Senior, metro role with general Data Science visibility but specialized ML/risk needs increases medium competition.
Role requires deep ML, MLOps, and domain-specific risk/telecom experience, making cross-industry transferability limited.
Explicit 12+ years and 2+ years management plus mandatory ML, big-data, and MLOps tech stack makes filters strict.
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Lead and own the Data Science strategy and technical roadmap for Truecaller for Business, translating business vision into executable data initiatives with defined KPIs.
Architect, scale, and deploy ML models in production to drive measurable business outcomes and ensure model accuracy and system uptime.
Manage and mentor a team of Data Scientists and Analysts, collaborating across Product, Platform Engineering, and Leadership to define product scope, risk policies, and drive data-driven solutions.
12+ years of total experience in Data Science/Machine Learning with at least 2 years in engineering management.
Bachelor's or Master's degree in Data Science, Machine Learning, Computer Science, Statistics, Mathematics, or related quantitative field.
Proficiency in Python, SQL, and modern ML frameworks like scikit-learn, TensorFlow/PyTorch, and experience with large-scale data querying tools (BigQuery, Spark).
Experience with MLOps pipelines, containerization (Docker/Kubernetes), and scaling real-time predictive models.
Experienced leader capable of managing cross-functional collaborations and aligning Data Science initiatives with business and product goals.
Strong technical background in high-volume data environments, real-time fraud mitigation, or B2B analytics, with hands-on expertise in modern ML engineering.
Skilled communicator able to translate complex statistical models to non-technical stakeholders and define actionable technical constraints.