Senior Data Scientist at Analytic Partners designing advanced data science and AI solutions. Collaborating with teams to drive innovations and impact on products and clients.
About the role
- Data Scientist supporting management consultants conduct data analysis and providing strategic decision-making insights. Involves data processing, model development, and collaborative problem-solving with clients.
Responsibilities
- Support the team of management consultants in conducting data analyses, contributing to scenario diagnostics, identifying opportunities, and supporting strategic decision-making.
- Collect, clean, and preprocess data from multiple sources (internal and external), ensuring data quality, consistency, and integrity.
- Develop, test, and validate analytical models, including predictive and prescriptive approaches, with a focus on delivering business value.
- Translate analytical results into actionable insights through the preparation of clear, concise, and visually appealing reports and presentations.
- Participate in client meetings to gather requirements, understand business problems, and present data-driven solutions.
- Collaborate effectively within multidisciplinary teams, maintaining clear communication with both technical and non-technical stakeholders.
Requirements
- Bachelor’s degree in Business Administration, Economics, Engineering, Statistics, or related fields.
- Postgraduate degree or specialization in Data Science, Data Analytics, or related areas.
- Hands-on experience in Machine Learning projects applied to real-world problems.
- Proficiency in Python for data analysis, statistical modeling, and solution development.
- Knowledge of SQL for extracting, manipulating, and analyzing data in relational databases.
- Familiarity with modern data environments, including distributed processing tools (e.g., Spark) and cloud platforms (AWS, Azure, or GCP).
- Availability to work in a hybrid model and for occasional travel.
- Strong command of Python for developing data pipelines and analytical models.
- Experience with Machine Learning libraries (e.g., scikit-learn, statsmodels, or similar).
- Experience with anomaly detection techniques and/or time series modeling.
- Experience with SQL and relational databases.
- Experience deploying models, either via APIs (FastAPI, Flask) or batch pipelines.
- Experience integrating with APIs and ingesting external data.
- Experience building and maintaining data pipelines (ETL/ELT).
- Knowledge of geospatial data analysis or urban data.
- Experience with process automation and applications involving Generative AI (LLMs).
- Practice monitoring models in production, including drift detection and re-training strategies.
Benefits
- Health insurance
- Dental insurance
- Meal allowance
- Transportation voucher
Job title
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