Hybrid - San Bruno, CA
Contract.
Responsibilities
- Perform hands-on modeling and complex analyses using Python, SQL and/or R
- Build and enhance marketing mix models to connect the impact of marketing tactics and business short-term and long-term outcomes
Description
We are seeking an experienced data science individual contributor to enable deep insights and capabilities to our clients through advanced analytics and machine learning techniques (e.g. predictive modeling, segmentation, etc)
Responsibilities
- Perform hands-on modeling and complex analyses using Python, SQL and/or R
- Build and enhance media mix models to connect the impact of marketing tactics and business short-term and long-term outcomes
- Run optimization and simulation scenarios to help provide the marketing investment and allocation recommendations
- Present media mix insights to different levels of senior clients
- Explain complex modeling approaches in simple terms and develop compelling narratives that connect modeling results with business problems
- Partner with cross-functional team to streamline data science solutions
- Integrate disparate data sources and leverage state-of-the-art analytics best practices in order to deliver integrated actionable insights to partners and senior leadership around digital marketing optimization
Minimum Qualifications
- Master's degree in statistics, economics, operations research, engineering, or related field
- 6+ years of industry experience in data science, measurement, marketing strategy & analytics
- Strong communication skills to 'tell a story' that provides insight into the business
- Proficient coding skills (SQL/Python/R) and database knowledge
- Extensive experience with predictive modeling algorithms
- Strong project management skills, including managing technical resources and multiple priorities & milestones
- You have a passion for working in a fast-paced agile environment
- A collaborative mindset and sense of curiosity
Thank you,
Ashutosh Pasbola, Assistant Manager
Syntricate Technologies Inc.
Phone#: (781)-552-4332| Email to: [email protected]
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