Work closely with your business to identify issues and use data to propose solutions for effective decision making
Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation.
Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
Querying databases and using statistical computer languages: R, Python, SLQ, etc.
Visualizing/presenting data through various Dashboards for Data Analysis, Using Python Dash, Flask etc.
Test data mining models to select the most appropriate ones for use on a project
Work in a POSIX/UNIX environment to run/deploy applications
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
Develop custom data models and algorithms to apply to data sets.
Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
Horizon scan to stay up to date with the latest technology, techniques and methods
Coordinate with different functional teams to implement models and monitor outcomes.
Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
General Expectations:
Able to create algorithms to extract information from large data sets
Strong knowledge of Python, R, Java or another scripting/statistical languages to automate data retrieval, manipulation and analysis.
Experience with extracting and aggregating data from large data sets using SQL or other tools
Strong understanding of various NLP, and NLU techniques like Named Entity Recognition, Summarization, Topic Modeling, Text Classification, Lemmatization and Stemming.
Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, etc.
Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
Experience with Jupyter / Pandas / Numpy to manipulate and analyse data
Knowledge of Machine Learning techniques and their respective pros and cons
Strong Knowledge of various Data Science Visualization Tools like Tableau, PowerBI, D3, Plotly, etc.
Experience using web services: Redshift, AWS, S3, Spark, DigitalOcean, etc.
Proficiency in using query languages, such as SQL, Spark DataFrame API, etc.
Hands-on experience in HTML, CSS, Bootstrap, JavaScript, AJAX, jQuery and Prototyping.
Hands-on experience on C#, Javascript, .Net
Experience in understanding and analyzing data using statistical software (e.g., Python, R, KDB+ and other relevant libraries)
Experienced in building applications that meet enterprise needs – secure, scalable, loosely coupled design
Strong knowledge of computer science, algorithms, and design patterns
Strong oral and written communication, and other soft skills critical to collaborating and engage with teams
Skills:- Natural Language Processing (NLP), Computer Vision, Neural networks, Artificial Neural Network (ANN), Predictive modelling, Machine Learning (ML), Data Science, Deep Learning and recommendation algorithm