DMI is looking for a Data Science Manager who will support our customer’s product, sales, leadership, and marketing teams with insights gained from analyzing data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building, and implementing models, using/creating algorithms, and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Primary responsibilities fall into the following categories:
- Plan: Deeply understand the business requirements and priorities and work with other stakeholders to identify high-impact and feasible roadmap areas for the team from time to time. The fact that the business teams may not understand how data science could help their work makes this very challenging.
- Execute: Own the deliverables of the team and be in charge of the estimation and planning done by the team making sure that the dependencies are tracked correctly, and results are produced in an efficient and timely manner. Also take care of regular feedback and performance appraisals.
- Guide:Act as a technical guide to the team helping them in translating the business problems to the most appropriate mix of specific machine learning or data analysis tasks. Also be a mentor to the team members helping them with career planning and growth.
- Facilitate: Be an evangelist of best practices, the right tools and effective collaboration. Proactively create a great working environment where each individual brings out the best they can offer.
- Communicate:Be the point of contact for the team’s work for the business teams and senior management. Create and deliver effective presentations at various stages of the projects to different audiences involved.
- Grow:As new opportunities come, proactively do talent planning and drive the hiring activities.
If you meet most of the following requirements, you are likely to be a great fit for the position:
- You have a strong academic background in statistics and machine learning. The typical candidate has a Bachelor’s or Master’s degree in Math, Statistics, Computer Science, Physics or such quantitative fields or has done a program from a business school in marketing, analytics etc. with a focus on quantitative approaches.
- Overall 8+ years with most of your experience were related to data and data analysis. You have worked on a variety of complex data analysis and modeling problems, gathering a great deal of practical wisdom on how to apply these techniques to real world scenarios.
- 2+ years, you have been in a technical leadership position responsible for the output of a team. The team(s) you were leading successfully executed and delivered multiple data science projects end to end under your leadership.
- You are competent enough to roll up your sleeves and get things done as a data scientist when the situation demands. You have a wide range of statistical and machine-learning tools under your belt. These include linear models for regression and classification, multi-level models, factor analysis & PCA, discriminant analysis, support vector machine, decision tree ensembles & bootstrap, neural networks, mixture models & clustering algorithms, and so on. You are proficient in at least one programming language commonly used for data analysis (like R/Python), and you are cozy with SQL.
- Previously worked on business analytics problems like customer churn, lifetime value estimation, targeted marketing, personalized offers, etc. And experienced in designing & analyzing controlled experiments for targeted interventions in the field
- Masters or Doctorate in relevant domain.
- Possess strong data visualization skills using programmatic tools (e.g. ggplot2, shiny, d3.js) and other visualization frameworks like victory, highcharts etc. This will be a strong plus.
- Knowledgeable on different database and data warehousing systems like MySQL, Amazon Redshift, BigQuery, Teradata
- Experienced in working with large data sets, with big data processing tools like MapReduce, Spark, Hive, etc. Have data engineering skills to do preprocessing, cleaning and transformations.