Senior Data Scientist

Job Summary

The role of a Senior Data Engineer is critical in designing, developing, and maintaining robust data infrastructure and systems that enable efficient and accurate data processing, storage, and retrieval. Senior Data Engineers play a pivotal role in ensuring the availability, integrity, and security of data to support data-driven decision-making and enable advanced analytics and machine learning initiatives.

Job Responsibilities

• Support leadership with research on key business initiatives and challenges.
• Perform analyses on large sets of data to extract actionable insights that will drive decisions, with a particular focus on our marketing and sales strategy. Engineer novel data sets and features that shed new light on the dynamics of consumer choices.
• Define success measures and build tools that predict and track the performance of strategic projects.
• Communicate data-driven insights and recommendations to non-technical audiences, through clear visualizations and presentations.

Job Requirement

• Degree in Computer Science/Engineering, Mathematics, Statistics, Economics, or another quantitative field; an advanced degree is desirable.
• (4+ years) of relevant experience analyzing complex data with SQL, Python, and/or R.
• Modeling, algebra, and statistical knowledge are strong preferences. Feature engineering for machine learning models is a real plus.

Experience:

• Experience with visualizations and dashboarding (e.g., Power BI or similar BI software) is a strong preference.
• Experience creating and scheduling datasets is highly valued. Knowledge of Azure, GCP, and Airflow is a plus.
• Strong understanding of data transformation tools such as DBT is a plus.
• Good understanding of Tensorflow and Apache Kafka
• Sound understanding of Microsoft SQL Server Integration Services and SQL Server Analysis Services

Required Knowledge, Skills & Competencies:

• Proficient in statistical analysis, data mining, and machine learning techniques.
• Experience with exploratory data analysis, feature engineering, and dimensionality reduction.
• Expertise in developing and implementing advanced predictive models and algorithms.
• Proficiency in statistical analysis techniques, hypothesis testing, and experimental design.
• Knowledge of A/B testing methodologies and experience with experimental data analysis.
• Understanding of the industry or domain in which the data scientist operates.
• Familiarity with specific business problems, metrics, and challenges relevant to the organization

Person Specification

• Effective verbal and written communication skills to present complex data findings in a clear and concise manner.
• Strong interpersonal skills and the ability to work collaboratively in cross-functional teams.
• Willingness to share knowledge, support colleagues, and contribute to a positive team environment.
• Commitment to maintaining data confidentiality, integrity, and ethical standards.
• Professionalism, reliability, and the ability to handle sensitive or confidential information with discretion.