Sr. Specialist, Data Scientist at Hikma Pharmaceuticals PLC

, Amman, Jordan -

Full Time

Start Date

Immediate

Expiry Date

26 Sep, 26

Salary

0.0

Posted On

28 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Azure Databricks, SQL, PySpark, Machine Learning, NLP, LLM, Power BI, Tableau, ETL/ELT, TensorFlow, PyTorch, Pandas, NumPy, Scikit-learn, Selenium

Industry

Description

Location: Amman, Jordan Job Type: Full-time Hashtag: #LI-AA2 About Us : For over 45 years, Hikma Pharmaceuticals has been putting better health within reach, every day, by creating high-quality medicines and making them accessible to those who need them. We are helping to shape a healthier world that enriches all our communities, and our global team of 9,500+ empowered employees are central to this mission. As a trusted and reliable partner of over 800 high-quality generics, specialty and branded pharmaceutical products, we are driven to improve access to medicine. Through our 29 manufacturing plants, 3 R&D hubs across the MENA, North America and Europe, our footprint allows us to play a critical role in serving patients. Description: We are looking for a talented Sr. Specialist. Data Scientist to join us. At Hikma you’ll be supported by a culture of progress and belonging where people are encouraged to develop, wellbeing is prioritised and our inclusive approach values contributions from all. We’re seeking candidates who embody our values: Innovative, driven to keep learning; Caring, genuinely compassionate in their work; and Collaborative, eager to solve problems together. If you want to be part of a team that cares about impact, this is the place for you. Key Responsibilities: Develop and deploy machine learning models to enhance financial forecasting, anomaly detection, and predictive analytics. Work with large datasets from SAP ECC, ERP systems, and external sources, integrating them into Azure Databricks for analytics. Collaborate with finance, accounting, and business teams to understand challenges and develop data-driven solutions. Design and optimize data pipelines to enable ML model training, validation, and deployment. Utilize LLM, NLP, time-series analysis, and deep learning where applicable to extract insights from structured and unstructured data. Develop interactive dashboards and visualizations to communicate insights to finance and business stakeholders. Ensure data quality, governance, and compliance while handling sensitive financial data. Utilize automation tools such as Selenium to streamline data collection and processing workflows Qualifications: We are looking for candidates whose experience and skills align closely with the qualifications outlined below: Minimum: Bachelor’s in Data Science, Computer Science, Statistics, Mathematics, or a related field. Preferred: Master’s degree in Data Science or a related field. At least 4-7 years’ experience in data science and machine learning. Experience in a Finance department is plus. Skills: Strong proficiency in Python (including Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch). Experience with Databricks and Azure Databricks for large scale data processing and ML model deployment. Hands-on experience with SQL and working with relational databases. Knowledge of big data processing frameworks such as PySpark. Expertise in ETL/ELT processes and working with structured and unstructured datasets. Experience with data visualization tools such as Power BI, Tableau. Strong problem-solving, analytical, and critical-thinking skills. Experience with LLMs and NLP-based solutions for data enrichment and smart automation. Proficiency in English, both written and verbal, for effective communication with finance and business stakeholders. Learn more about Hikma in Jordan hikma-jordan-factsheet-aug-2025-en.pdf

Responsibilities

Develop and deploy machine learning models to improve financial forecasting, anomaly detection, and predictive analytics. Design data pipelines and interactive dashboards to provide data-driven insights for finance and business stakeholders.