Senior Data Scientist Insights - Marketing

Key Skills

C Programming, C++, Cloud computing, Data science techniques, Java Programming, Machine learning techniques, MATLAB Programming, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

As a Senior Data Scientist you’ll be part of a data science team, and work with stakeholders throughout the company, to generate understanding, strategy and guide key decision making based on data. You’ll spend your time doing practical data science work to transform complex data sets into pragmatic insights which you provide through skilled story-telling. You are expected to combine sound business understanding, data handling, programming, statistical modeling and data visualization to derive actionable information from broad sets of data while valuing pragmatism over perfection.

The successful candidate will join one of the Data Science & Analytics teams in our Marketing organization. They will be responsible for analyzing and reporting on various marketing channels & activities, leveraging the data from various inhouse built models and experimentation. They will be key in ensuring that data is leveraged with maximum impact, as well as take the lead on projects.

B.Responsible

• Transform large, complex datasets into pragmatic, actionable insights
• Identify and autonomously prioritize impactful strategic business problems, translate them into feasible data problems and solve them effectively by applying suitable statistical data analysis and modeling methods
• Identify, source and organize data required for the solution and prepare it in a way that makes it fit for use
• Identify key (senior) stakeholders and manage them proactively through effective communication and addressing their needs
• Use expert skills in data handling, programming, statistical modelling, data visualization and storytelling to drive actions from stakeholder
• Design and interpret quantitative experiments to objectively drive long-term strategic business decision making
• Have the capacity to thrive in our fast-paced environment, adapt quickly and take ownership of their work
• Challenge ideas and methods while working together with talented, highly skilled team members. Ensure quality of their own and others’ work, by making them reproducible and replicable and by validating through peer review
• Coach, mentor and direct other Data Scientists in all of the above responsibilities
• Design, evolve, and guard the data direction and information architecture for their tracks or department
• Act as force multiplier by thinking of and implementing ways to make other data professionals more effective, contribute significantly to the
• community of their area and connect their area to the rest of the business
• Act as a go-to data science authority for senior business stakeholders of their area and think a few quarters ahead in terms of analytical planning
• Own end-to-end processes of data science projects of wide scale (ie. with stakeholders from multiple business areas), while self-prioritizing and delivering at high velocity
• Convey complex analysis results clearly and with conviction to all levels of stakeholders and influence leadership in their area of responsibility to take decisions with data

B.skilled

• Master degree, PhD, or equivalent experience in a quantitative field (Statistics, Mathematics, Econometrics, Computer Science, Physics, Engineering, Bioinformatics, or similar)
• 5+ years (Master degree)
• 2+ years (PhD)
• Expert in solving real problems using data mining techniques and with statistical rigor
• Expert technical skills regarding data analysis, statistics, machine learning and programming. Strong working knowledge of Hadoop, Spark, SQL, Python and/or R.
• Excellent communication skills
• Expert in translating business problems into data problems
• Strong stakeholder management (senior stakeholders)
• Expert data visualization skills
• Strong skills in storytelling with data
• Expert in Statistical Methods (e.g. Testing, GLM, Inference), Statistical/Machine Learning (e.g. Dimension Reduction, Clustering, Neural networks, Regularisation, Bagged/Boosted methods), Time Series, Natural Language Processing etc

Strong knowledge of data management (engineering, data pipelines, workflows)

Expert knowledge of the possibilities and limitations of different types of data analysis and/or data science modelling

B.offered

We are a performance-based company that offers career advancement and lucrative compensation, including bonuses and stock potential. We also offer what we call the -Booking Deal- with other competitive perks and benefits. IT also has regular hackathons, training and attends/speaks at global conferences.