ML Engineer​/Statistician​/Data Scientist At Fulton, MD

Data Scientist

Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Develop custom data models and machine learning algorithms to apply to data sets
• Use predictive modeling to increase and optimize customer experiences, revenue generation, risk mitigation, fraud identification, ad targeting and other business outcomes

The candidate must demonstrate the following technical skills:

• Machine Learning, Artificial Intelligence, Statistical Modeling, Data Analysis, Predictive Analysis, Data Manipulation, Data Mining, Data Visualization and Business Intelligence
• Adept in statistical programming languages like Python, R and SAS including Big Data technologies like Hadoop, Hive, HDFS, Map Reduce and No
  
  SQL Based Databases
• Proficiency in Python data extraction and data manipulation, and widely used python libraries like Num Py, Pandas, and Matplotlib for data analysis
• Proficiency and experience in the use of using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets
• Experience in training and testing data using various Machine Learning algorithms like Linear & Logistic Regression, Naïve Bayes, Decision Trees, Random Forests, Clustering, SVM, Neural Networks, Principle Component Analysis, and Bayesian
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world applications, advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Knowledge of Recommender Systems
• Strong familiarity in working with various statistical concepts such as Hypothesis Testing, t-Test, and Chi
  - Square Test, ANOVA, Statistical Process Control, Control Charts, Descriptive Statistics and Correlation Techniques
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Strong interpersonal and communication skills

Preferred (but not mandatory)

Skills and Experience:

• Knowledge of and experience in the banking/finance industry
• Experience with distributed data/computing tools:
  Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Familiarity with neural networks and deep learning techniques – RNN/LSTM, CNN, ANN
• Coding knowledge and experience with several languages
• Experience with data visualization software such as Tableau, Qlikview, MATLAB, Microsoft Power BI, etc.
• Experience analyzing data from third-party providers
• Knowledge and experience working in Agile environments including the Scrum process

Summary of Technical Skills – (A successful candidate should possess all or majority of these skills)

• Languages
  - Python, R, T-SQL, PL/SQL
• Packages/libraries
  - Pandas, Num Py, Seaborn, Sci Py, Matplotlib, Scikit-learn, MLlib, ggplot2, Rpy2, caret, dplyr, RWeka, gmodels, NLP, Reshape2, plyr.
• Machine Learning
  - Linear Regression, Logistic Regression, Decision trees, Random forest, Association Rule Mining (Market Basket Analysis), Clustering (K-Means, Hierarchal), Gradient decent, SVM (Support Vector Machines), Deep Learning (CNN, RNN, ANN) using Tensor Flow (Keras).
• Statistical Tools
  - Time Series, Regression models, splines, confidence intervals, principal component analysis, Dimensionality Reduction, bootstrapping
• Big Data Hadoop, Hive, HDFS, Map Reduce, Pig, Kafka, Flume, Oozie, Spark
• BI Tools Tableau, Amazon Redshift, Birst
• Data Modeling Tools Erwin r, Rational Rose, ER/Studio, MS Visio, SAP Power designer
• Databases MySQL, SQL Server, Oracle, Hadoop/Hbase, Cassandra, DynamoDB, Azure Table Storage, Natezza
• Reporting Tools MS Office (Word/Excel/Power Point/ Visio), Tableau, Crystal reports XI, SSRS, IBM Cognos
  7.0/6.0.

Other Requirements

• Eligible to work in the United States (a valid H1B, Green Card or US Citizenship or other type of work visa)
• Work Location – Client site
• Copies of education and technical certifications will be required at the time of interview
• Two professional references will be required before final hiring decision