Expand and optimize data pipeline architecture on cloud platform
Perform data preparation (ETL), data cleansing on large and complex data sets from multiple sources for data analysts and data scientists
Work with business units to identify data that is relevant for analytic
Work with developers to define data tagging requirements
Ensure quality of data and keep track of data lineage
Qualification
3+ years of experience in data engineer or data architect role
Experience in relational database (SQL) and NoSQL databases.
Familiar with big data technologies (e.g. Hadoop)
Experience with Python, PySpark
Experience in data pipeline and workflow management tools (e.g. Luigi, Airflow) and stream processing
Communication skills including the ability to understand business process in any area in detail
Experience with machine learning models in production is a plus
Experience/Interest in the marketing, content marketing and financial domain is a plus
Data Analyst
Responsibilities
Work closely with business units to create reports and dashboards as business needs
Define and track metrics (KPI) for projects and market campaigns
Perform data mining to extract actionable insights from large and variety of datasets
Identify problems, trends and business opportunities through analysis of complex datasets
Qualification
2+ year of experience in data analyst field
Bachelor’s Degree in Statistic, Mathematics, Computer Science or related fields
Proficiency in Excel, SQL and Python
Experience with any BI tools (e.g. Power BI, Tableau)
Communication skills including the ability to understand business process in any area in detail
Knowledge of data science is a plus
Experience/Interest in the marketing, content marketing and financial domain is a plus
Data Scientist (Business Development)
Responsibilities
Engage with business teams to identify opportunities and improvement of product development, marketing techniques and business strategies with data science knowledge
Discover hidden insights in both structured and unstructured data applying statistical or machine learning techniques
Extract customer behavior and create customer single view from large dataset
Develop predictive model to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes
Perform data preparation (ETL), data cleansing on large and complex data sets from multiple sources if needed
Qualification
2+ years of experience in data science
Bachelor’s or Master’s Degree in Data Science, Statistic, Computer Science or related fields
Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark
Expert in SQL and Python
Experience in PySpark is a plus
Knowledge of a variety of statistical techniques and machine learning techniques
Excellent technical and analytical skills with experience solving real-world problems using data and providing practical business insights
Strong communication skill to present insights with data
Experience/Interest in product development, marketing, content marketing is a plus
Data Scientist (ML Investment)
Responsibilities
Develop predictive models for a variety of asset classes and indexes in global markets using advanced machine learning techniques
Participate in investment committee and provide investment strategies based on predictive models
Design trading algorithms that produce maximum alphas
Maintain and improve FINNOMENA Best-In-Class product
Apply alternative data (e.g. news, tweets) in investment decision and modeling
Qualification
2+ years of experience in investment research, financial modeling and analysis
Bachelor’s or Master’s Degree in Engineering, Computer Science, Mathematics, Financial Engineering or any other related field
Knowledge of a variety of statistical techniques and machine learning techniques
Knowledge of portfolio management is a plus
Have a research scientist mindset
Have a strong interest in global financial markets