Marketing Data Scientist

Webuyanycar.Com-posted about 1 year ago

Full-time

Springfield, PA

Motor Vehicle and Parts Dealers

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The Marketing Data Scientist will play a crucial role in shaping the marketing strategy and decision-making processes through advanced data analysis, predictive modeling, and machine learning techniques. This position is focused on deriving insights that will directly influence marketing campaigns, enhance customer engagement strategies, and contribute to overall business growth. A strong understanding of marketing analytics and the ability to translate complex data into actionable insights is essential for success in this role.

Utilize advanced data mining, statistical analysis, and machine learning techniques to identify trends, patterns, and insights from complex marketing data.
Develop predictive models and algorithms to optimize marketing campaigns, customer segmentation, and targeting strategies.
Collaborate closely with marketing teams to design experiments, analyze results, and provide actionable recommendations for improving campaign effectiveness and ROI.
Conduct deep-dive analysis to understand customer behavior, preferences, and lifetime value, leveraging these insights to personalize marketing efforts.
Build dashboards and visualizations to communicate key metrics and performance indicators to stakeholders, enabling data-driven decision-making across the organization.
Stay current with industry trends and best practices in marketing analytics, data science, and machine learning, applying them to enhance marketing strategies.
Work cross-functionally with the analytics team, IT team, and business stakeholders to ensure data quality, integrity, and accessibility for marketing analytics purposes.
Validate the impact of marketing campaigns through experiments and causal analysis.

Master's Degree (or equivalent level preferred) in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
Proven experience (3 years or more) in a data science or similar role within a commercial business, preferably consumer-facing.
Strong proficiency in programming languages such as Python or R, and experience with statistical analysis tools (e.g., SAS, SPSS, or similar).
Hands-on experience with machine learning techniques (e.g., regression, clustering, decision trees, neural networks) and frameworks (e.g., TensorFlow, scikit-learn).
Experience with data visualization tools (e.g., Tableau, Power BI) and database querying languages (e.g., SQL).
Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, Google Cloud).
Familiarity with creating data analysis plans and executing A/B testing methodologies.
Excellent analytical and problem-solving skills with the ability to interpret and communicate complex data analysis results effectively with strong attention to detail.
Strong business acumen with proven experience of applying data science techniques to business problems to drive increased revenue or introduce operational efficiencies.
Proven ability to effectively communicate and present findings and recommendations to non-technical stakeholders.

Proficient with company-based systems, Microsoft Windows and Office Suite applications.
Possess a strong desire to know how and why things work, inclined toward sustainable and manageable solutions.
Have self-awareness of strengths and opportunities, ability to introspect, and self-develop by engaging in continuous learning.
Proven ability to work independently and collaboratively in a fast-paced environment, with a proactive and results-oriented approach.

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