At Talkdesk as a Data Scientist, you will be creating the future of customer interactions. You will be tapping into data about human communication to find ways to improve day to day life for everybody who ever needed customer support, i.e., people like you.
- Work on large real world datasets using machine learning and statistical analysis tools to understand underlying structure, gain insights and explain them in clear and simple language;
- Data preparation, cleaning, and model training and evaluation;
- Research and develop data driven prototypes for engineering adoption;
- Research and propose new ways to extract value from data;
- Design and run experiments to improve the Talkdesk user experience;
- Develop highly reliable and scalable systems that go into real products;
- Designing state of the art data science algorithms and machine learning modules;
- Identifying and Integrating multiple data sources, cleaning data and making sure that data is consistent.
- MSc or PhD in Computer Science, Mathematics or Statistics;
- Strong knowledge of data analysis fundamentals, data structures, and algorithms;
- Experience with machine learning and/or statistical analysis techniques;
- Statistical knowledge and proficiency with statistical analysis tools like R or SAS;
- Experience with distributed databases and query languages like SQL, CQL or Pig;
- Programming experience with scripting languages such as Python or Ruby;
- Deep understanding of computer science fundamentals, data structures, and algorithms;
- Experience and insight into statistical and machine learning models such as regressions, Markov, decision trees, clustering, neural networks, convolutional networks, deep learning, graphs, LDA, SVM;
- Experience with machine learning tools and open source packages (e.g. Mallet, Tensor Flow);
- Strong written and verbal English communication skills.
Nice to have / Pluses:
- Experience with Big Data ML toolkits, such as Mahout, SparkML or H2O, Hadoop, Spark, Flink, Kafka;
- Experience with core Java;
- Experience working with distributed systems and NoSQL technologies;
- Experience with Amazon Redshift/Snowflake;
- Good understanding of Lambda and Kappa Architecture, along with its advantages and drawbacks;
- Experience with Cloudera/MapR/Hortonworks;
- Big Data Processing.