We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve the business.
- Ability to take lead and work in a trustworthy working environment.
- Partner with the required teams and get seamless outputs.
- Should be curious to learn more and collaborate whenever needed.
- Ability to independently manage projects and report/present efforts to clients.
- Strong communication skills.
- Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products.
- Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.
- Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.
- Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.
- Analyze data for trends and patterns, and Interpret data with a clear objective in mind
- Implement analytical models into production by collaborating with software developers and machine learning engineers.
- Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems.
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred.
- Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc.
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (i.e., Java/Python, SAS).
- Understanding of reporting & data visualization tools such as Business Objects, PowerBi and Tableau.
- Understanding of ETL framework and ETL tools including Alteryx and Microsoft SSIS.
- Digital marketing analytics tools including Google 360, Google Analytics, Google Tag Manager and Adobe Marketing Suite.
- Intermediate understanding of databases such as SQL Server, Oracle and SAP.
- Proficiency with data mining, mathematics, and statistical analysis.
- Advanced pattern recognition and predictive modeling experience.