Data Science Manager

One of our leading clients has a requirement for a Data Science Manager to manage their high-performing team and work closely with the software engineering teams

Responsibilities:

·       Manage a team to drive measurable value.

·       Conceptualise, analyse, build, test, and implement models that utilize various and diverse data sets to solve problems related to the employment and recruiting industries.

·       Build and implement machine learning models, testing frameworks, and visualisations to make timely decisions and influence the product roadmap.

·       Proactively research data and identify opportunities in the data to drive the product roadmap.

·       Evaluate data's big picture to solve business problems rather than focusing on metrics alone.

·       Understand human behavior and know what to look for in the data.

·       Communicate concisely and persuasively with engineers and product marketers.

·       Help identify ways to improve data quality and analysis.

Requirements:

·       Experience managing data science/analytics teams.

·       Significant prior success as a Data, Product, or Decision Scientist working on challenging problems at scale.

·       6+ years of industry experience, with expertise in Data Science, Machine Learning.

·       Proficient in Python, Pandas, SQL.

·       Bachelors / Masters degree / PhD in Computer Science, Statistics, Mathematics, Artificial Intelligence, Quantitative Methods, Cognitive Science, or a closely related quantitative field.

·       Expertise in data mining, statistical modeling, and machine learning.

·       Passion for optimizing Business performance, Client Lifecycle and Client Experience with data.

·       Full stack experience in data collection, aggregation, analysis, visualization, productization, and monitoring of data science products.

·       Deep expertise in applied machine learning, preferably in digital advertising, auctions, or bidding systems.

·       Strong track record of delivering high business value in a fast-paced dynamic environment.

·       Experience in client lifecycle management (e.g. retention; optimization) will be an advantage.

·       Experience running controlled online experiments and taking data-driven decisions for improving machine learning-based products. Preferably in non-independent settings, like marketplaces.

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