Data Science Intermediate Analyst - Hybrid

Key Skills

Analytical and Problem solving, Data Analytics, Data science techniques, Financial Risk, Planning and organization, Python Programming, R Programming, SAS, SQL

Job Description

The Data Science Intermediate Analyst role will support tactical and strategic initiatives and projects focused on scenario effectiveness advancement as well as operational efficiency. The initiatives and projects will emphasize agile low cost solutions designed to provide speed to market and support a longer term strategic solution. This role will require to work with Regional Lead who will direct and support global team members during implementation and on an ongoing basis as needed.

Responsibilities:

• Support global/regional lead responsible for investigating and researching the AML processes and tools identifying efficiency and effectiveness opportunities.
• Own and Supports BAU execution of systematic identification and suppression of false positives.
• Supports new product risk assessment under guidance of regional lead.
• Supports tactical and strategic initiatives and projects focused on scenario effectiveness advancement as well as operational efficiency.
• Provide clear actionable metrics and visualization for Sr. Mgmt. Present effectively.
• Analysis employing available technology to identify patterns, red flags or typologies of interesting behavior.
• Synthesize information into knowledge by identifying relevant trends and issues.
• Prepare presentation materials for decision makers.
• Participate in the development, testing, training and implementation of new or enhanced tactical solutions or strategic system applications.
• To ensure availability of analysis’ evidence is documented & support in audit related matters when applicable.
• To support in minimizing the audit breaching & aligned with Risk Management team to manage risk expose for all activities/projects.

Qualifications:

• Minimum Bachelor’s degree with 4+ years of professional work experience
• minimum 2+ years in data analysis experience required; Qualitative and quantitative intelligence analysis in the business (financial, national intelligence, or technology industry is highly preferred.
• Strong working knowledge of SQL, R, SAS, or Python programming languages.
• Must have the ability to effectively communicate (both written and verbally) through all levels of the organization including the ability to translate technological concepts into easily understood presentations.
• Methodical analysis and problem solving skills including the ability to translate complex analytical concepts into actionable intelligence recommendations.
• Demonstrate creative and innovative experience and the ability to think outside the box.
• Mature, self-starting, self-motivated and capable of making independent decisions.
• Demonstrate a seasoned career progression.
• Proficient in PC desktop software, with emphasis on MS Office products.
• Financial / banking background is a plus.

Education:

• Bachelor's Degree in relevant Banking/Finance/Technical Field.
• Data Science, Data Analyst, Python Programming course and certification is plus.