ABOUT MSCIMSCI is a leading provider of investment decision support tools to clients worldwide, ranging from large pension plans to boutique hedge funds. We offer a range of products and services - including indexes, portfolio risk and performance analytics - through several internationally recognized brands MSCI, Barra, RiskMetrics, Real Estate, FEA, InvestorForce, etc.
Applied Data Intelligence Team (ADI) is responsible for data management, data quality and building innovative data products. It has two major sub groups:
Data Desk:This part is responsible for providing solutions for the full lifecycle of data content management: vendor procurement, quality analysis, usability, scalability and new product feasibility studies. We cover a growing set of asset classes and data categories including among others, market data, fundamental data, analyst forecasts, corporate actions and MSCI proprietary data.
Data Science:This part closely works with data desk and business to understand and build AI based solutions to help maintain data quality. They are also involved in new product development and improving operational efficiency using various machine learning techniques.
POSITION OVERVIEW – Associate / Senior Associate (Data Science)
We are looking for candidates who will help us discover the information hidden in vast amounts of data and help make smarter decisions to deliver better and error free products. You will be involved in building specific AI tools to automate certain processes for our internal clients (various product teams).
Responsibilities:Identify valuable data sources and automate collection processes
Undertake preprocessing of structured and unstructured data
Analyze large amounts of information to discover trends and patterns
Build predictive models and machine-learning algorithms
Combine models through ensemble modeling
Present information using data visualization techniques
Propose solutions and strategies to business challenges
Collaborate with engineering and product development teams
Necessary Skills and Qualifications:
3 - 9 years of experience in developing and designing Analytical solutions and models
Proficient in PYTHON programming
Prior experience in deploying machine learning models into production
Preferred Qualifications: Computer Science / Statistics / Mathematics / Econometrics or another quantitative field
Application of statistical/mathematical methods in analyzing data.
Good communication skills (written and oral) and proficiency in creating presentations.
An independent worker who can drive certain parts of the work with minimal oversight
Comfortable working with a wide range of stakeholders and functional teams
Desired Skills:Practical understanding and application of data science and machine learning techniques like: Linear & Logistic Regression, KNN, SVM, PCA, Random Forests, Markov Chains, Clustering (DBSCAN, K-means, etc.), Deep Learning (CNN, RNN, Autoencoders, Transformers, etc.)
Text Analysis and Natural Language Processing (NLP) – Exposure to chatbots or dialogue systems, machine translation, comprehension of text, text summarization
Hands on experience withcomputational packages (NumPy, SciPy, Pandas, Sklearn, statsmodels, Keras,TensorFlow, PyTorch, RASA etc.) and visualization tools
Strong statistics/computer science skills (e.g. probability, algebra, data structures and algorithms)
Proficiency with AWS or Azure cloud computing environments
Experience in working with GPUs to develop models
Publications or presentations in recognized Machine Learning and Data Mining journals/conferences
Knowledge in business intelligence, quantitative finance and descriptive statistics
Reinforcement Learning
Have strong interest or work experience in Finance – Stocks, capital markets, bonds, alternate asset classes
