Data Scientist

  • Engineering
  • Remote job

Data Scientist

Job description

Unifonic is a customer engagement platform that enables organizations to delight customers with remarkable omnichannel experiences. By unifying communication channels, messaging apps, and chatbots, Unifonic streamlines conversations at every touchpoint throughout the customer journey.

Data Scientist

The Data & Analytics team at Unifonic is looking for a strategic and number-driven Data Scientist to take part in growing our analytical & insight capabilities to shape the future of our organization. In this role, your insights will tell us what we are doing right, what we are doing wrong, and what we should do next. You will work closely with the Data Analytics Senior Director to provide business recommendations anchored on data, facts, and insights. You will be working within a team of analytics experts, conceptualizing, designing, and building quantitative models, decision algorithms, KPIs, metrics, and other analytical products to enable cross-functional decision-making.

The successful candidate should possess an entrepreneurial mindset, a strong sense of ownership, no fear of getting their hands dirty, and a razor-sharp focus on getting things done.

The responsibilities of the Data Scientist include, but are not limited to:

  • Conceptualize, design, and implement machine learning modules, algorithms and analytical products focused on commercial problem statements.

  • Conceptualize required data pipelines in support of machine learning modules.

  • Deploy models in production environments for large-scale applications.

  • Source, cleanse, and analyze large disparate data sets.

  • Develop and maintain data science best practices across various departments.

  • Collaborate closely with Data Engineering and Business Analytics team members to build comprehensive business-focused solutions.

  • Develop a deep understanding of Unifonic’s unique set of problem statements across a diverse set of business processes.

  • Visualize and communicate recommended solutions in a humanely-friendly manner to business stakeholders.



  • Bachelor’s degree in Quantitative Science: Statistics/Mathematics; Computer Science; or equivalent.

  • 3-5 years of hands-on work experience in developing and deploying various types of analytical models.

  • Experience in Python with experience in common data science toolkits, such as NumPy, Pandas, PySpark, Scikit-Learn, Tensorflow, PyTorch, Keras, rasa, BERT, spaCy.

  • Extensive expertise in data science skills including SQL, R, hypothesis testing, data cleansing, data augmentation, data pre-processing techniques, dimensionality reduction, mathematics, probability, and statistics (e.g. conditional probability, Bayes rule, and Bayes nets, Hidden Markov Models, etc.).

  • Experience with techniques such as GLM/Regression, Boosting, text mining, social network analysis, Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modeling and optimization, evaluation metrics, classification, and clustering.

  • Experience using distributed infrastructure components such as S3, Spark, Hive/Hadoop, etc.

  • Hands-on experience with data visualization/analytics platforms such as Tableau, Looker, PowerBI, or similar.

  • A successful history of manipulating, processing, and extracting value from large disconnected datasets.

  • Experience with ‘commercial’ problem statements such as user churn prediction, fraud detection, recommendation engines, margin optimization, or similar is highly desirable.

  • Excellent problem-solving skills.

  • Fluent in English with excellent writing/editing and verbal communication skills.