Roles and Responsibility :–
- Experience in programming languages.
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Develop and drive complex projects using Advanced analytic techniques. Translate conceptual questions into data-driven analyses to allow leaders to make informed decisions
- Liaison with on-site and client teams to understand various business problem statements analytical requirements
- Drive for value proposition with best in class industry practices & latest algorithms
- Oversee & improve machine learning models developed by the team & identify scope for model improvements & best practices.
- Candidates must have experience in developing Machine learning models.
- In-depth knowledge of machine learning, deep-learning processing techniques.
- Develop AI/ML solutions/applications leveraging the latest industry and academic advancements.
- Experience with data cleansing, feature creation, feature selection, and value imputation.
- Broad experience building different types of advanced analytic solutions, including some of the following: time series analysis, cluster analysis, tree-based algorithms, generalized linear models, or neural networks.
- Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- Develop Predictive analytics solutions on the different types of financial information
- Develop and operationalize reporting to measure the impact of implemented changes
- Lead efforts to optimize our business
- Drive large scale, complex cross-functional initiatives in support of the senior leadership key strategic priorities
- Identify key indicators of economic shifts, business and/or policy changes and prepare situational playbooks to allow leaders to focus on mission-critical decisions
- Excellent communication skills and the ability to manage multiple, diverse stakeholders across business areas and leadership levels.
- Exercise sound judgment to diagnose and resolve problems within an area of expertise.
Qualifications:
- Degree in Statistics, Applied Mathematics, Computer Science or other technical disciplines
- 6+ years of relevant experience in a Data Science
- Effective communication skills, both written and verbal; ability to “tell the story” and develop executive-level presentations with guidance
- Demonstrated ability to work effectively and collaboratively with teams
- Experience in descriptive & predictive analytics
- Strong understanding of statistical analysis, predictive modeling, and data engineering techniques
- Ability to develop analytical approaches to answer high-level questions and develop insightful recommendations
- A client-service mindset and a desire to take on tough and challenging projects. The scope and variety of work will change frequently depending on the current project portfolio
- An understanding of finance and financial analysis is preferred
- Working knowledge on the financial information
- Languages & Tools: Good to have Alteryx, Dataiku, Cognos Business Intelligence & OLAP: Oracle BI: OBIEE, Oracle Analytics, Cloud (OAC), Oracle Report Builder (ORB); ETL: Matillion, Talend, TOAD, SQL Plus, SQL Navigator, SQL, Loader, OWB, ERwin, Decision Stream, MS Visual Studio; MS Office/Office 365, SharePoint; Crystal Reports; IBM Visual Age for Java, IBM WebSphere Application Server/Studio, Languages
