Machine Leaning & Data Scientist (Statistics, Machine learning, python, Sql, Spark, Experimentation)

Machine Leaning & Data Scientist (Statistics, Machine learning, python, Sql, Spark, Experimentation)

This position works within a data science team, and with stakeholders within the Partner Services department, to generate understanding, strategy and guide key decision making based on data. They spend their time doing practical data science and machine learning work to transform complex data sets into pragmatic insights which they provide through skilled story-telling. They are expected to be a unique hybrid of data hackers, business analysts, communicators and mentors that maintain a strong customer focus and values pragmatism over perfection.

Key Responsibilities

• Transform large, complex datasets into pragmatic, actionable insights.
• Translate business problems into feasible data problems and solve them effectively by applying suitable statistical data analysis and modelling methods.
• Identify, source, and organize data required for the solution and prepare it in a way that makes it fit for use.
• Design and interpret quantitative experiments, quasi-experiments, or causal inference studies to estimate the impact of initiatives and objectively guide key business decision-making.
• Identify key stakeholders and manage them proactively and independently through effective communication and addressing their needs.
• Use data visualization skills and storytelling to drive actions from stakeholders.
• Thrive in a fast-paced environment, adapt quickly, and take ownership of work.
• Challenge ideas and methods while working collaboratively with talented, highly skilled team members.
• Ensure quality of their own and others? work by making it reproducible and replicable, validating through peer review.
• Convey complex analysis results clearly and with conviction to all levels of stakeholders.
• Leverage Data Science for impact while incorporating scalability, reproducibility, and long-term orientation in their work.

Level of Education

• Master's degree or PhD in a quantitative field (Computer Science, Statistics, Econometrics, Physics, Mathematics, Engineering, Bioinformatics, etc.).

Requirements of Special Knowledge/Skills

• Minimum 6 years of experience in a relevant role.
• Experience in solving real-world problems using data mining techniques with statistical rigor.
• Strong expertise in validating hypotheses/models and measuring impact/incrementality of interventions (treatment) through:
  • A/B testing, quasi-experiments, and various causal inference methods.
• Expertise in establishing incremental impact at an average and group/individual level:
  • Uplift modelling or heterogeneous treatment effect.
• Proven experience in creating impact within an organization through full-fledged implementation of data science solutions.
• Strong working knowledge of:
  • SQL, Python/R, Git.
• Experience working with Big Data (preferably PySpark) and Data Management (preferably Snowflake, SageMaker).
• Strong data visualization and storytelling skills.
• Knowledge of the possibilities and limitations of different types of data analysis and/or data science modelling.
• Excellent communication and presentation skills with the ability to convey complex ideas in a simplified manner.
• Ability to navigate ambiguity and align stakeholders with varied viewpoints.
• Strong skills in translating business problems into data problems while applying business context in solutioning and storytelling.

Preferred/Bonus Experience

• Experience with attribution modelling and related marketing measurement techniques is a big plus.
• Experience measuring campaign/channel effectiveness is a big plus.
• Experience with deep learning/neural networks is a plus.
• Experience working in a product and/or marketplace organization is a plus.

Please send your CV or call Toni to discuss further.
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We champion differences in technology recruitment and work with clients who actively wish to diversify their talent force - ALL applicants are welcome to apply.