As a Data Science Tech Lead, you will build our data capabilities end to end: collecting, analyzing, driving insights, and delivering machine learning solutions that enhance our offerings. You will play a pivotal role in building the organization’s “data muscle,” empowering Operational and Network teams to use data for smarter decisions, operational excellence, and innovation. The role requires a seasoned professional with deep expertise in data strategy, analytics, and governance, paired with a hands-on mindset to deliver results.
responsibilities :
Ensure key business drivers are captured during the design of Machine Learning solutions in collaboration with product stakeholders.
Lead data science projects and mentor data scientists, establish standards for code quality, experimentation, documentation, and reproducibility.
End-to-end ownership of ML models on Data Science platform, from data ingestion and feature engineering to training, deployment, monitoring, and retraining.
Drive data strategy and governance: data contracts, quality, privacy, security, and compliance across the model lifecycle.
Ensure reliability of models in production (SLOs/SLAs, observability, retraining schedules, alerts).
Extract and analyze network and business data to identify trends, detect anomalies, and recommend improvements in service performance and customer experience.
Apply advanced analytical techniques and develop predictive models and algorithms that support telecom operations across the value chain.
Collaborate with cross-functional teams including engineering, product, and operations.
Maintain and enhance the model development environment including pipelines and orchestration frameworks.
Visualize and explain the outcomes of the work in a way that is understandable for diverse audiences
requirements-expected :
Minimum 5 years of proven industry experience in data science or applied machine learning.
Solid business acumen, strong customer centric mindset and strategic thinker who can balance big picture strategy with tactical needs of day-day execution.
Strong programming skills in Python.
Expert knowledge of supervised and unsupervised machine learning methods.
Hands-on experience with ML libraries and frameworks such as Scikit-Learn, TensorFlow, PyTorch.
Proficient with big data tools (e.g., Spark, Hadoop) and orchestration tools.
Solid foundation in data analytics, data visualization, data mining, statistics, and probability theory.
Experience with SQL and relational databases.
Familiar with agile methodologies and software development practices (Git, JIRA, Confluence).
Experience working in cloud environments (Data Robot, AWS and GCP are a plus).
Understanding of big data ecosystems and ETL processes.
Previous experience working with telecom datasets (e.g., network KPIs, customer behavior) and stakeholder management skills.
Strong problem-solving skills and a proactive, detail-oriented mindset.
Excellent communication skills with the ability to present findings to diverse audiences.
Fluent in English (written and spoken).
benefits :
sharing the costs of sports activities
private medical care
sharing the costs of professional training & courses
life insurance
remote work opportunities
flexible working time
corporate products and services at discounted prices
