Data Scientist

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Job Description: Data Scientist

The Opportunity:

The Data Scientist plays a pivotal role in the Delivery Excellence team, contributing expertise in statistics, data modeling, machine learning, and operations research. This position requires a strong analytical mindset, a passion for machine learning, and a knack for problem-solving. The ideal candidate will drive the development of early warning systems, deploy machine learning techniques to unveil insights, and excel in use case development, taking projects through deployment while defining success criteria & Organization level impact.

Key Responsibilities:

• Collaborate with cross-functional teams to align data analysis with business objectives and identify data-driven opportunities.
• Collect, cleanse, and pre-process extensive datasets from diverse sources, ensuring data quality and integrity.
• Apply advanced statistical and machine learning techniques to analyse data, identifying meaningful patterns, trends, and insights.
• Develop predictive models, classification algorithms, and other machine learning solutions tailored to solve specific business challenges.
• Design and execute experiments for hypothesis testing, model validation, and algorithm optimization.
• Utilize data visualization tools to convey intricate findings to both technical and non-technical stakeholders.
• Enhance data collection methods, integrate novel data sources, and optimize overall data infrastructure.
• Collaborate closely with software engineers to seamlessly deploy models and algorithms into production systems.
• Stay updated on the latest advancements in data science and machine learning, fostering continuous improvement and innovation.
• Develop and automate data collection processes, identifying valuable sources.

Skills and Attributes for Success:

• Your skills and experience will be impactful in the following ways:
• Strong proficiency in programming languages like Python, R, and Julia for data analysis, modeling, and visualization.
• Solid grasp of statistical concepts and their practical application to real-world data challenges.
• Proficiency in data mining, machine learning, and operations research.
• Familiarity with languages such as R, SQL, Python; bonus points for familiarity with Scala, Julia, Java, or C++.
• Experience with business intelligence tools (e.g., Power BI) and data frameworks.
• Strong mathematical skills, including statistics and matrix algebra.
• Analytical mindset coupled with business acumen.
• Extensive experience with various machine learning techniques, encompassing regression, classification, clustering, and time-series analysis.
• Proficiency in popular machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Hands-on expertise in data manipulation and SQL/NO SQL querying, along with related database technologies.
• Familiarity with data pre-processing techniques, feature engineering, and dimensionality reduction.
• Excellent problem-solving skills, especially with large, intricate, and unstructured datasets.
• Exceptional communication skills to convey technical concepts to both technical and non-technical stakeholders.
• Exposure to cloud platforms (e.g., AWS, Azure, GCP) and big data technologies is advantageous.
• Previous experience in a similar role or industry-specific knowledge is a plus.

Qualifications:

Master’s degree/ Formal Qualification in Analytics/ in a quantitative discipline such as Computer Science, Statistics, Mathematics, or related field.

• Approximately 14+ or more years of experience in a comparable role.

What We Look For:

• Passionate, committed, determined, and outcome oriented.
• Analytical mindset with a curiosity for uncovering insights within data.
• Self-motivated and proficient in both independent and team-based work.
• Adaptability to evolving project requirements and emerging technologies.
• Detail-oriented with a commitment to delivering accurate and high-quality results.
• Strong organizational skills, adept at multitasking.
• Demonstrate the ability to extract insights from diverse and unstructured data sources, effectively addressing uncertainty and ambiguity.
• Innovate techniques to pre-process and integrate data from various domains, contributing to a more holistic understanding of the problem at hand.
• Encourage out-of-the-box thinking in model design, advocating for unconventional approaches that challenge the status quo.
• Drive the exploration of cutting-edge methodologies and techniques, such as incorporating insights from unrelated fields to develop novel solutions.
• Excel in simplifying complex findings and insights derived from intricate datasets, ensuring clear and actionable communication to stakeholders.
• Exhibit the ability to connect seemingly unrelated data points, fostering a deeper understanding of intricate patterns and correlations.

Benefits:

• Opportunities for professional development, including conferences and workshops.
• Collaborative and innovative work environment.
• Opportunity to make a significant impact by driving data-driven decision-making.

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