DATA SCIENCE AND ANALYTICS
We help customers make informed decisions in their businesses leveraging our core data analytics expertise, thereby creating business value from raw data
We have helped customers translate observations to shared knowledge and contribute to strategy. We show how to solve core business problems operating with algorithmic complexity.
We use raw data to build a predictive algorithm and with use heuristics. Our quantitative technique in finding solutions to many business problems involving building analytic models.
We carry rich experience in Predictive Modeling, Structural Equation Modeling, Survey designing, Data mining, Regression Analysis (Linear to non-linear), Statistical Analysis Interpretations, Hypothesis Testing or Estimation
Data Exploration Analysis and Insight
Mining data insight and building data product expressing textures, dimensions, and correlations in data that can be expressed mathematically.
We use classical and Bayesian statistics, inferential techniques and machine learning algorithms through use of Creativity and ingenuity skills to build and find clever solutions to problems.
We conduct data visualization using tableau through detailed analysis and performing insights from source data
Advanced Algorithms Machine Learning
We consider ourselves algorithmic thinker with the ability to break down messy problems and recompose them in ways that are solvable. We have a strong mental comprehension of high-dimensional data, tricky data control flows pieces and putting pieces together to build a cohesive solution.
Our rich experience in SQL, Python, R, and SAS. On the periphery are Java, Scala, Julia, and others has helped us able to prototype quick solutions, as well as integrate with complex data systems.
Data Product Engineering
Our experience in building “data products" has been processing data to algorithmically-generated results.
Diving in at a granular level to mine and understand complex behaviors, trends, and inferences. It’s about surfacing hidden insight that can help enable companies to make smarter business decisions.
Our mature experience in analytical creativity helps us to investigate leads , try to understand pattern or characteristics within the data using quantitative technique in order to get a level deeper – e.g. inferential models, segmentation analysis, time series forecasting, synthetic control experiments
- Experience in Python / R Language
- Data scraping and API Design
- Data normalization and distribution
- Knowledge of probability and statistics.
- Experience in Data visualization and related tools.
- Experimental design and adaptive experimentation methods.
- Data collection and cleaning
- Relational database management with SQL or NoSQL document database topology
- Applied Mathematics – Linear Algebra and Calculus
- Algorithms and data structures – Sorting, Trees, Graphs, and Data Topology Design
- Linear regression models and Classifiers
- Principal Component Analysis
- Supervised learning methods – KNN Classifiers; Random Forest Classifiers; Logistic, Ridge, and Lasso Regression Methods; Support Vector Machines; Boosting Models
- Unsupervised learning methods – K-means, mean-shift, spectral, and affinity clustering methods
- Neural Networks and Deep Learning – Supervised NN; Unsupervised NN; Recursive NN; Convolutional NN; Long Short-Term Memory NN; Deep Learning; Reinforcement Learning
- Natural Language Processing – LSA, PCA, LSTM, Vectorization, N-Grams, and Contextual Analysis Methods
- Computer Vision – Tensorflow, Keras; OpenCV