About Snapp

Snapp is the pioneer provider of ride-hailing mobile solutions in Iran that connects smartphone owners in need of a ride to Snapp drivers who use their private cars offering transportation services. We are ambitious, passionate, engaged, and excited about pushing the boundaries of the transportation industry to new frontiers and being the first choice of each user in Iran.

About Team:

Data Science is at the heart of Snapp’s products and decision-making. As a member of the Data Science team, you will work in a dynamic environment, where we embrace moving quickly to build the world's best transportation and many other services. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products. We work closely with many teams of the company to improve their products and decisions.

About Role:

As a Data Scientist, Decisions, you will leverage data and rigorous, analytical thinking to shape the company's product and business decisions. You will identify and scope opportunities, shape priorities, recommend solutions, design experiments, and measure impact. You will bring a quantitative mindset to decision-making in partnership with product, business, and operations stakeholders throughout the organization.

Responsibility:

•  creation and development of predictive models using AI/ML technologies, including the installation and monitoring of production performance. 
• Partner with business units and cross-functional teams to understand business requirements and integrate additional data needed for creating advanced models. 
• Perform data feature engineering to collect and structure data, enhancing the modeling and analytical framework.
• Collaborate closely with engineers to deploy models in production, both in real-time and batch processes, and systematically track and optimize model performance.
• Act as a subject matter expert on machine learning and predictive modeling, providing guidance and insights.
• Drive technical innovation through active research and the application of new theories, techniques, and technologies.
• Mentor junior data scientists, providing guidance, support, and monitoring project progress.
• Communicate non-technical reports detailing project outcomes and insights to stakeholders.
• Formulate and oversee data-driven projects to advance business objectives, ensuring alignment with organizational goals.
• Develop structured frameworks, scalable tools, and organizational processes to enhance company planning and product performance.
• Design and analyze experiments, communicate results, and make launch decisions.
  
• Establish metrics to measure the health of products and the rider and driver experience.

• Minimum of 5 years of experience as a Data Scientist or in a similar role, with a track record of progressively increasing responsibilities.
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Proficient in Python and its libraries: Pandas, NumPy, SciPy, StatsModels, Scikit Learn, Seaborn, and Matplotlib.
• Advanced SQL knowledge and experience working with both relational and non-relational databases, including query authoring and working familiarity with various other databases and datasets.
• Comprehensive understanding of the model build lifecycle, including feature selection and optimization, model selection and validation, and ongoing model maintenance.
• Extensive knowledge of statistics, including statistical tests, distributions, regression, maximum likelihood estimators, etc.
• Experience in online experimentation and statistical analysis.
• Experience with automated machine learning tools and workflows, such as Airflow, and other relevant technologies.
• Excellent interpersonal skills, highly organized, able to multitask, and a strong team player.
• Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholder.

• Knowledge and experience in image processing and NLP is a plus.
• Experience with systems like Spark, Hive,Kafka, and stream processing is a plus.
• Strong understanding of deep learning and experience with deep learning libraries is a Plus