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āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
8 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Data Analysis, Tableau, Excel
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Work closely with stakeholders to understand business requirements, identify opportunities, and whitespace to commercialize data-driven insights and solutions.
- The candidate will need to lead data analysis and sales pitching for the Annual Media planning process, and have good commercial awareness and communication skills to be able to connect with multiple stakeholders.
- Break down business questions into analytical frameworks, and being able to talk the language of technical teams as well as commercial stakeholders is a key requirement ...
- The candidate will need to lead the development of end-to-end data lead media solutions, and media measurements to keep ahead of the media industry standards and own roadmap to deploy and modernize media measurements across different media platforms, channels, and mechanics.
- Candidates should have some idea of offline and online SSP and DSP platforms and architecture, and market direction to strategically build and improve media solutions, either owned or in partnership with external parties.
- Be proactive and co-own the go to market strategy along with commercial stakeholders for multiple media channels/ and other data commercialization initiatives, and proactively help plan the right focus areas for the team, develop solutions and products to help build the roadmap and pipeline for commercial opportunities.
- Develop and implement predictive models, statistical algorithms, and machine learning models to support business needs.
- Develop and implement data visualizations using PowerBI/ Data Studio/QuickSight/ Tableau/ Excel to effectively communicate insights to stakeholders.
- Collaborate with cross-functional teams, including business analysts, product managers, and developers, to implement data-driven solutions.
- Stay up to date with emerging technologies, marketing technology platforms, omni-channel media and industry trends to identify new opportunities for improving data analytics and applications.
- Mentor and coach junior data scientists and data analysts to develop their skills and expertise.
- Bachelor s or Master s degree in data science/ engineering/ statistics/economics/ computer science/ mathematics, or a related field is a requirement.
- MBA/Business degree with strong background in technical understanding and hands-on expertise is preferable.
- Online media experience will be a strong advantage.
- 8+ years of experience as a data scientist or data analyst in marketing across any industry is a requirement.
- Strong proficiency in Python/ Pyspark/ SQL/ R is a requirement.
- Strong experience in story telling from data, analysis and insight is required.
- Commercial understanding, and having a balanced approach for go-to-market strategy is a requirement.
- Experience with machine learning algorithms and statistical modeling is a bonus.
- Strong communication skills and the ability to collaborate with cross-functional teams is a requirement.
- Proven ability to work independently and manage multiple projects simultaneously is a requirement.
- The candidate must display a high sense of accountability and be agile in handling high value projects, and be able to motivate the team to deliver as a shared objective with the commercial plan.
- Experience in mentoring and coaching junior/ senior DA/ DS is a requirement.
āļ§āļąāļāļāļĩāđ
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āļāļąāļāļāļķāļ
āļĒāļāđāļĨāļīāļ
āļāļēāļāļāļ°āļāļī, āļāļĢāļļāļāđāļāļ, āļāļēāļĢāļāļąāļāļāļēāļĢ
āļāļēāļĢāļāļąāļāļāļēāļĢ
āļāļąāļāļĐāļ°:
Power BI, Statistics, Python
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop and implement key performance indicators (KPIs) to measure campaign effectiveness, in-app conversion rates, and product performance.
- Analyze customer behavior patterns to identify opportunities for product recommendations and cross-selling.
- Build and maintain data dashboards and reports using Power BI to visualize and communicate insights to stakeholders.
- Collaborate with marketing and commercial teams to optimize campaigns and drive business growth.
- Analyze in-app user behavior to optimize user experience and conversion rates and identify opportunities for product placement and cross-selling within the app.
- Develop and implement predictive models for sales forecasting, campaign performance, customer churn, and customer lifetime value.
- Build and deploy machine learning models for recommendation systems, personalized product recommendations, and customer segmentation.
- Conduct A/B testing and experimentation to optimize website and in-app experiences.
- Collect, clean, and validate large datasets from various data sources for e-commerce platform and marketing channels.
- Master s degree or PhD in Statistics, Computer Science, Mathematics, or a related field.
- Strong programming proficiency in Python or R.
- Expertise in machine learning algorithms and techniques (e.g., regression, classification, clustering, time series analysis).
- Experience with data mining and statistical modeling tools.
- Proficiency in data visualization tools (e.g., Power BI, Tableau).
- Strong problem-solving and critical thinking skills.
- Excellent communication and presentation skills.
- Experience in the e-commerce industry.
- Knowledge of SQL and database management systems.
- Experience with cloud-based data platforms (e.g., AWS, GCP, Azure).
- Understanding of A/B testing methodologies.
- Experience with mobile app analytics tools like Mixpanel.
2 āļ§āļąāļāļāļĩāđāļāđāļēāļāļĄāļē
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āļĒāļāđāļĨāļīāļ
āļĻāļĢāļĩāļĢāļēāļāļē, āļāļĨāļāļļāļĢāļĩ, āļāļĢāļīāļŦāļēāļĢāļāļĨāļīāļāļ āļąāļāļāđ / āļāļĢāļīāļŦāļēāļĢāđāļāļĢāļāļāđāļŠāļīāļāļāđāļē
āļāļĢāļīāļŦāļēāļĢāļāļĨāļīāļāļ āļąāļāļāđ / āļāļĢāļīāļŦāļēāļĢāđāļāļĢāļāļāđāļŠāļīāļāļāđāļē
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Data Analysis, Automation, Python
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Work with stakeholders throughout the organization to understand data needs, identify issues or opportunities for leveraging company data to propose solutions for support decision making to drive business solutions.
- Adopting new technology, techniques, and methods such as machine learning or statistical techniques to produce new solutions to problems.
- Conducts advanced data analysis and create the appropriate algorithm to solve analytics problems.
- Improve scalability, stability, accuracy, speed, and efficiency of existing data model.
- Collaborate with internal team and partner to scale up development to production.
- Maintain and fine tune existing analytic model in order to ensure model accuracy.
- Support the enhancement and accuracy of predictive automation capabilities based on valuable internal and external data and on established objectives for Machine Learning competencies.
- Apply algorithms to generate accurate predictions and resolve dataset issues as they arise.
- Be Project manager for Data project and manager project scope, timeline, and budget.
- Manage relationships with stakeholders and coordinate work between different parties as well as providing regular update.
- Control / manage / govern Level 2 support, identify, fix and configuration related problems.
- Keep maintaining/up to date of data modelling and training model etc.
- Run through Data flow diagram for model development.
- EDUCATION.
- Bachelor's degree or higher in computer science, statistics, or operations research or related technical discipline.
- EXPERIENCE.
- At least 5 years experience in a statistical and/or data science role optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis, Expertise in advanced Analytica l techniques such as descriptive statistical modelling and algorithms, machine learning algorithms, optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis.
- Expertise in advanced analytical techniques such as descriptive statistical modelling and algorithms, machine learning algorithms, optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis.
- Experience using analytical tools and languages such as Python, R, SAS, Java, C, C++, C#, Matlab, SPSS IBM, Tableau, Qlikview, Rapid Miner, Apache, Pig, Spotfire, Micro S, SAP HANA, Oracle, or SOL-like languages.
- Experience working with large data sets, simulation/optimization and distributed computing tools (e.g., Map/Reduce, Hadoop, Hive, Spark).
- Experience developing and deploying machine learning model in production environment.
- Knowledge in oil and gas business processes is preferrable.
- OTHER REQUIREMENTS.
1 āļ§āļąāļāļāļĩāđāļāđāļēāļāļĄāļē
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