You will help our client discover information hidden in Big Data, build Hadoop data lake environment to improve analytics and help make smarter decisions to deliver even better products and services.
Primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with the company’s wide variety of offerings.
The successful candidate will advocate, evangelize and build data-fuelled analytic based predictions that help customers improve and optimize their experience. Mine data and become the expert on datasets. You will provide insight into leading analytic practices, design and lead iterative learning and development cycles, and ultimately produce new and creative analytic solutions that will become part of our core deliverables.
You will work with cross-functional team members to identify and prioritize actionable, high-impact insights across a variety of core business areas. Lead applied analytics initiatives that are leveraged across a breadth of solutions. Support research, design, implement and validate cutting-edge algorithms to analyze diverse sources of data to achieve targeted outcomes.
As part of the primary data science team, you will provide expertise on mathematical concepts for the broader applied analytics team and inspire the adoption of advanced analytics and data science across the entire breadth of the organization.
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Doing ad-hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
Skills and Qualifications
- Ph.D. or Master’s Degree in operations research, applied statistics, data mining, machine learning, physics or a related quantitative discipline. You have a deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms.
- Experience delivering world-class data science outcomes, you solve complex analytical problems using quantitative approaches with your unique blend of analytical, mathematical and technical skills.
- Passionate about asking and answering questions in large datasets, and you are able to communicate that passion to product managers and engineers. Have a keen desire to solve business problems, and live to find patterns and insights within structured and unstructured data. Able propose analytics strategies and solutions that challenge and expand the thinking of everyone around you.
- You are expert in analyzing large, complex, multi-dimensional datasets with a variety of tools. You are accomplished in the use of statistical analysis environments such as R, MATLAB, SPSS or SAS. You have experience with BI tools such as Tableau, Microsoft BI or other. You’re as comfortable with relational databases as you are with Hadoopbased data mining frameworks. You are familiar with SQL, Python, Java and C/C++.
- You are expert in analyzing large, complex, multi-dimensional datasets with a variety of tools. You are accomplished in the use of statistical analysis environments such as R, MATLAB, SPSS or SAS. You have experience with BI tools such as Tableau and Microstrategy. You’re as comfortable with relational databases as you are with Hadoop-based data mining frameworks. You are familiar with SQL, Python, Java and C/C++.
- You desire a fast paced, test-driven, collaborative and iterative engineering environment. You love learning, data, scale and agility. You excel at making complex concepts simple and easy to understand by those around you. You’re driven to show the world the power of applied analytics.
- Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc.
- Experience with data visualization tools, such as D3.js, GGplot, etc.
- Proficiency in using query languages such as SQL, Hive, Pig
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- Good scripting and programming skills
- Data-oriented personality