Manager, Data Science

Manager, Data Science Job Description

• Understanding business objectives and developing analytical solutions that help achieve them, along with metrics to track their progress.
• Performing various exploratory data analysis to uncover trends, insights and develop strategies.
• Leveraging generative approaches to understand user behavior and metrics of interest.
• Designing and analyzing A/B tests and Multivariate tests.
• Analyzing data and developing predictive models using machine learning and deep learning.
• Collaborate cross-functionally across internal teams (marketing, product, technology, research, etc.) to evaluate opportunities that deliver business goals via data analysis and machine learning.
• Develop and promote a data driven approach by proactively identifying new potential analysis projects and highlight key opportunities to drive our organization forward.
• Share results and conclusions you draw to derive meaning from the data, and what business actions you think should be taken as a result of the analysis.
• Identify learnings from your analysis for how we can improve the collection and upkeep of our datasets.
• Enhancing data collection procedures to include information that is relevant for building analytic systems.
• Coordinate across departments and with our analytics providers to establish best practices and adhere to common design patterns, and work through your plans with others to troubleshoot potential issues upfront.
• Act as a role model throughout our team, but also our organization by maintaining the highest professional standards, promoting data governance, data management, creative thinking and pushing us to be always be our best.
• Manage a team of 3 to 4 data scientists, coach, and mentor them to achieve their full potential.

• Master's Degree required in Computer Science, Business Analytics, Data Analytics, or Data Science, Machine Learning, or related field with 3+ years Or Bachelor's Degree with 5+ years of professional work experience in data analysis and machine learning.
• 2+ years of experience managing analytics and data science teams
• Strong experience with communicating technical findings to relevant stakeholders and providing applicable business insights and recommendations.
• Proficient in SQL, writing queries, and reporting.
• Excellent scripting and programming skills with Python, R, etc. with hands-on experience.
• Proficiency with Python-based common data science toolkits such as Jupyter Notebooks, Numpy, Pandas, Scikit-learn, MatplotLib, Seaborn, NLTK, etc.
• Ability to write clean, reproducible, robust, and scalable analysis code.
• Good, applied statistics skills, such as distribution analysis, probability theory, statistical testing, regression, etc.
• Expertise in running exploratory data analysis, statistical modeling and data mining.
• Experience with designing and analyzing experiments (A/B tests and Multivariate tests).
• Excellent understanding of supervised and unsupervised machine learning techniques and algorithms, such as Clustering, Topic Modeling, K-Means, Naive Bayes, SVM, Decision Forests, Neural Networks, etc.
• Experience with data visualization tools, such as PowerBI and Tableau.
• Ability to run automated jobs to manipulate and store data from APIs and various cloud providers.
• Hands-on experience working with large data sets.

• Working experience with a deep learning frameworks such as TensorFlow or Keras.
• Understanding of special deep learning networks such as Convolutional Neural Networks, for computer vision.
• Experience developing recommendation engines using different techniques like collaborative filtering, content-based filtering, deep learning-based approaches, etc.
• Understanding of statistical decision theory.