MSc in Finance and Data Analytics

Paris

 

INTAKE: September

Program Overview

The MSc in Finance and Data Analytics at ESSCA School of Management is a specialized program designed to equip students with a strong foundation in both finance and data analytics. It focuses on merging financial expertise with cutting-edge data analytics skills to meet the demands of the evolving financial landscape.

Curriculum: The curriculum integrates courses covering financial analysis, investment management, risk assessment, econometrics, and data analytics techniques. Students learn to apply data analytics tools and methodologies to financial decision-making processes.

Research Focus: ESSCA encourages research initiatives exploring the intersection of finance and data analytics, such as financial modeling using data analytics, predictive analytics in finance, machine learning applications in financial markets, and big data in finance.

Industry Engagement: The program emphasizes industry engagement through collaborations with financial institutions, data analytics firms, and financial technology companies. Students engage in real-world projects, internships, and workshops conducted by industry professionals.

Global Perspective: Recognizing the global nature of financial markets, the program adopts a global perspective. It examines international financial regulations, global market trends, and the application of data analytics in diverse financial contexts.

Pollster Education

Location

Paris

Pollster Education

Score

IELTS 6.5

Pollster Education

Tuition Fee

€ 17900

Postgraduate Entry Requirements

Academic Qualification: Applicants for postgraduate programs usually need a bachelor's degree or an equivalent qualification from a recognized institution. The entry requirement may specify a minimum score of 60% or higher in the previous academic degree.

English Language Proficiency:

  • IELTS Scores: For postgraduate studies, the required overall band score may range from 6.5 to 7.0, with minimum band scores of 6.0.

Students must provide:

  • academic marksheets & transcripts
  • letters of recommendation
  • a personal statement - SOP
  • passport
  • other supporting documents as required by the university.

Work experience: Some postgraduate courses may require relevant work experience in the field.

It's important to note that entry requirements can vary by program and may change over time. Additionally, some programs may have additional requirements, such as interviews, portfolios, or work experience.

ESSCA School of Management is supporting international students through various scholarship opportunities. These scholarships are designed to recognize academic excellence, promote diversity, and provide financial assistance to talented individuals seeking to pursue their education at ESSCA. 

Merit-Based Scholarships: ESSCA offers merit-based scholarships to outstanding international students with exceptional academic achievements. These scholarships often cover a percentage of tuition fees and are awarded based on academic records, leadership qualities, and extracurricular involvement.

Need-Based Financial Aid: The institution provides need-based financial aid to support students who demonstrate financial need. These scholarships aim to ensure that deserving candidates have access to quality education regardless of their financial background.

Diversity Scholarships: ESSCA values diversity and encourages students from various cultural, geographical, and socioeconomic backgrounds to apply. Diversity scholarships are available to promote an inclusive learning environment, fostering a global perspective among students.

Country-Specific Scholarships: In certain cases, ESSCA offers scholarships tailored to students from specific countries or regions. These scholarships are intended to attract talent from diverse parts of the world and strengthen the international community at the school.

Partner Institution Scholarships: ESSCA has partnerships with various institutions and organizations worldwide. Through these partnerships, eligible students may have access to specific scholarships or exchange programs.

Graduates of the MSc in Finance and Data Analytics program at ESSCA School of Management possess a unique blend of financial expertise and data analytics skills, opening diverse career opportunities in the finance and analytics domains. 

  1. Financial Analyst: Conducts in-depth financial analysis using data analytics tools to evaluate investment opportunities, assess risk, and provide recommendations for financial decision-making.

  2. Quantitative Analyst: Applies mathematical and statistical models to analyze financial data, develops algorithms for trading strategies, and conducts quantitative research for investment firms.

  3. Data Analyst in Finance: Focuses on financial data interpretation, generates reports, and provides insights for financial planning, budgeting, and forecasting using data analytics.

  4. Risk Analyst/Manager: Analyzes and manages financial risks using data-driven methods, assessing market risks, credit risks, and operational risks for financial institutions.

  5. Investment Manager: Manages investment portfolios, makes strategic investment decisions based on data analysis, market trends, and risk assessments.

  6. Financial Consultant: Provides advisory services to businesses or individuals on financial strategies, leveraging data analytics to optimize financial operations and investments.

  7. Financial Technology (FinTech) Specialist: Works in FinTech firms, utilizing data analytics to develop innovative financial products, automated trading algorithms, or digital financial services.

  8. Business Intelligence Analyst: Applies data analytics to derive insights from financial data, supporting strategic business decisions and financial performance improvement.

  9. Market Research Analyst: Focuses on financial market trends, conducts market research using data analytics to identify opportunities or risks for businesses.

  10. Credit Risk Analyst: Assesses the creditworthiness of individuals or organizations, analyzing financial data to determine lending risks and establish credit policies.


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