Staff Data Scientist

Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out:

• We are trusted by over 450 million active users every month across 190+ countries
• We identify over 15 billion calls daily, helping users avoid spam and scams
• We are powered by a team of 450+ employees from 45+ nationalities

We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in.

As a Staff Data Scientist, you will be responsible for collecting, organizing, analyzing, and interpreting Truecaller data and drawing insightful conclusions with the aim of enhancing BU’s road map, business plan, and customer experience. You will possess a proactive mindset in tackling novel business problems, leveraging advanced analytical techniques and tools to extract valuable insights from large and complex datasets. 

You exhibit a strong inclination towards data exploration and hypothesis testing, with a focus on continuously improving the accuracy and efficiency of analytical models. You will work in close collaboration with the product, engineering, and platform team in order to identify and follow up on metrics, evaluate A/B tests and user behavior, and identify product insights. 

The role requires working both independently and proactively with identifying improvement opportunities as well as being involved in separate projects. The Data Scientist will act as an advisor to the BU's product improvement, strategy building, and management team by identifying and communicating data insight

• →Applying cutting-edge machine learning algorithms and statistical models to uncover meaningful insights from large and complex datasets.
• →Constructing predictive models that utilize historical data to forecast trends and anticipate future outcomes with accuracy and precision.
• →Collecting, organizing, analyzing, and interpreting all data and drawing insightful conclusions which enable us to work in a smarter way.
• →Create visual interpretations from data and explain graphs and charts with insightful notes and summaries.
• →Analyzing user data and assisting product development in finding new innovative ways of presenting and making use of data.
• →Collaborating with other BU's to identify business problems and develop data-driven solutions.
• →Support our management team in identifying, measuring, and following up on key metrics.
• →Providing regular, accurate, and comprehensive statistical reports.
• →Providing objective insight and analysis to influence decision making.
• →Ensuring quality of data and actively working on cleaning data to make sure of top notch relevance and accuracy.
• →Actively keep up to date on external market and data research and work towards adding data points from external sources to our own data in order to create a value added analysis.

• 10+ years of experience in Data Science OR relevant PhD + 1 years of industry experience.
• Data science background in digital advertising, marketing analytics, or ad-tech.
• Knowledge of machine learning algorithms focusing on regression, classifications, clustering, probability networks, association rules, deep neural networks, and reinforcement learning.
• Extensive experience with analytical and quantitative problem-solving.
• Experience with common analysis tools such as jupyter, open source or commercially available libraries.
• Programming knowledge in at least one language such as Python , along with excellent SQL skills.
• Hands-on experience with Python data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and Matplotlib/Seaborn etc.
• Familiarity with ML lifecycle management tools such as Kubeflow and MLflow is a strong plus.
• Experience in data modeling on Big Query, Hive/Spark/Hadoop/Kafka ecosystem.
• Knowledge of database modeling and data warehousing principles 

• Familiarity with Google Cloud Platform (GCP) and BigQuery will be a strong plus.
• Experience with data science best practices, design patterns, and SOLID principles.
• Hands-on experience in building large scale platforms & services using Scala, Kafka & Nosql stores.
• Experience with GCP or any other public cloud.
• Good English skills, oral and written

We will fill the position as soon as we find the right candidate, so please send your application as soon as possible. As part of the recruitment process, we will conduct a background check.

We only accept applications in English.