d) at Brillio

Berlin, Berlin, Germany

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

FinTech, PaymentsIndustries

Requirements

6+ years of total experience in a data-driven, quantitative, or machine learning role
Proven experience managing, mentoring, or formally leading a team of Data Scientists or analysts
Proficient in Python (pandas, scikit-learn, xgboost) and SQL (MySQL, Postgres, Snowflake), and data visualization tools like Tableau
Proven experience with general classification models (classical and deep learning), anomaly detection algorithms, and graph networks
Proven experience leading or contributing significantly to the deployment and productionizing of ML services, demonstrating a deep understanding of modern MLOps concepts like containerization and event-driven architectures
Expertise in managing both technical and executive/non-technical stakeholders to align priorities and gain buy-in
Strong problem-solving capabilities coupled with business understanding and the ability to translate complex business problems into the team’s analytical and technical requirements
Excellent communication and data storytelling skills, with a track record of maximizing the impact of the findings on organizational decision-making and cross-functional engagement
Experience with ML orchestration frameworks like Metaflow, Apache Flink and similar MLOps tools

Responsibilities

Lead and mentor a small, dedicated team of data scientists, guiding their professional development, managing project priorities, and ensuring the delivery of high-quality, impactful anti-fraud solutions
Apply extensive expertise in quantitative analysis, data mining, data science, and advanced ML to model debtor behavioral patterns, identify risk factors, and optimize Billie's real-time decision engine logic (hands-on and leadership role)
Work as a leader within cross-functional teams of data and software engineers, analysts, product managers, and business leaders to optimize Billie’s decision engine by improving its logic, introducing new data sources, and enhancing functionalities
Ensure the successful deployment and operationalisation of ML services, collaborating closely with Engineering on requirements for robust ML infrastructure, including containerization and event-driven architectures
Maximize the impact of findings on critical business decisions through excellent data storytelling and clear, actionable recommendations
Define the strategic roadmap, approve hypotheses for experimentation, and oversee in-depth analysis to understand debtor behavioral patterns and emerging fraud trends

Skills

Key technologies and capabilities for this role

Machine LearningData ScienceFraud DetectionQuantitative AnalysisData MiningRisk ModelingDecision EnginePythonLeadershipMentoring

Questions & Answers

Common questions about this position

What experience level is required for the Data Science Manager role?

The role requires 6+ years of total experience in a data-driven, quantitative, or machine learning role, along with proven experience managing, mentoring, or formally leading a team of Data Scientists or analysts.

What technical skills are needed for this position?

Proficiency in Python (pandas, scikit-learn, xgboost), SQL (MySQL, Postgres, Snowflake), and data visualization tools like Tableau is required, along with experience in general classification models, anomaly detection algorithms, graph networks, and deploying ML services.

Is this role remote or hybrid?

The position is hybrid.

What does the team structure look like for this role?

You will lead and mentor a small, dedicated team of data scientists within the broader Decision Science group, while working with cross-functional teams of data and software engineers, analysts, product managers, and business leaders.

What makes a strong candidate for the Data Science Manager position?

Strong candidates have 6+ years in data science or ML roles with team leadership experience, hands-on expertise in Python, SQL, ML models for fraud detection, and proven success in deploying ML services to production.

Brillio

Technology consulting for digital transformation

About Brillio

Brillio helps businesses with their digital transformation by providing technology consulting services. The company focuses on creating customized digital solutions that utilize artificial intelligence and cloud technologies to meet the specific needs of each client. This includes improving operational efficiency and enhancing user experiences through real-time responses and better workflows. Brillio serves a variety of clients, including large Fortune 500 companies, with a strong emphasis on the healthcare sector. Unlike many competitors, Brillio's approach is centered on developing bespoke solutions that give clients a competitive advantage, aiming to help them evolve into 'generative enterprises.' The company's goal is to drive significant improvements in business operations and outcomes through its consulting services and technology implementations.

Edison, New JerseyHeadquarters

2014Year Founded

LATE_VCCompany Stage

Consulting, AI & Machine Learning, HealthcareIndustries

1,001-5,000Employees

Benefits

Remote Work Options

Risks

High competition in tech may impact Brillio's talent acquisition and service scaling.

Over-reliance on healthcare exposes Brillio to sector-specific regulatory and funding risks.

Expansion into new markets may stretch resources, leading to potential operational inefficiencies.

Differentiation

Brillio specializes in bespoke digital solutions for diverse industries, focusing on AI and cloud.

The company is recognized as an Enterprise Innovator in healthcare payer services.

Brillio's Cloud and AI Studio aims to modernize enterprise IT systems and optimize workflows.

Upsides

Increased demand for AI-driven healthcare solutions boosts Brillio's market potential.

Expansion in India enhances service delivery and innovation through a growing tech talent pool.

Recognition in Open Banking IT Services highlights Brillio's role in financial digital transformation.

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