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Data Scientist Jobs (Hybrid work)

493 Job Offers

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Lead Data Scientist (Hybrid)
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Lead Data Scientist role in Chicago with Enova's Fraud Analytics team. Requires 5+ years in ML or quantitative modeling, hands-on fraud experience, and advanced Python/SQL skills. Hybrid schedule with strong benefits.
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106000.00 - 140000.00 USD / Year
Enova International
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Senior Data Scientist
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IDT seeks a Senior Data Scientist to build ML models from scratch and deploy them to real-time production. Work on fraud prevention, payment risk, and personalization with large-scale data. Remote B2B, 5+ years required.
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IDT
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Lead Data Scientist
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Lead Data Scientist role in New York with NBCUniversal's streaming team. Requires 5+ years in ML, deep learning, Python, and recommender systems expertise. Shape personalization models for Peacock and drive GenAI innovation.
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NBCUniversal
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Senior Data Scientist - AdTech / MarTech
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Senior Data Scientist role in Hyderabad for AdTech/MarTech. Requires 6+ years in data science, strong Python and SQL, plus expertise in identity resolution and third-party data quality evaluation.
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Blend360
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Senior Data Scientist – Fintech (Credit and Fraud)
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Senior Data Scientist role in Berlin fintech: own credit and fraud models end to end, from data pipelines to deployment and monitoring. Requires strong Python, SQL, AI tooling and real-time decisioning experience.
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Delivery Hero
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Data Scientist II
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Join Carousell Group in Singapore as a Data Scientist II. Build and ship ML models end-to-end across search, recommendations and trust & safety. Requires 3+ years ML experience, Python, SQL and Mandarin or Cantonese proficiency.
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Peak XV Partners
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Data Scientist
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Nielsen seeks a Data Scientist in Mexico City to drive data-driven insights for consumer measurement. Requires 2-3 years of experience, Python skills, and statistical knowledge. Enjoy flexible work, LinkedIn Learning, and volunteer time off.
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NielsenIQ
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Senior Data Scientist
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United Kingdom, Manchester / Hybrid
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AJ Bell
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Lead Data Scientist - AdTech / MarTech
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Blend360
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Associate Data Scientist I
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abbvie
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Data Scientist II
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Peak XV Partners
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Lead Data Scientist
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NBCUniversal
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Data Scientist
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Inetum
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Data Scientist
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bet365
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Data Scientist
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bet365
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Lead Data Scientist, Sports
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bet365
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Lead Data Scientist, Sports
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bet365
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Data Scientist
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India, Bengaluru, Karnataka, India
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Coface
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Data scientist - OTA (Databricks / PySpark)
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alten
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Senior Data Scientist / Generative AI Specialist
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Devoteam
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About the Data Scientist role

Explore the dynamic and in-demand field of data science and discover the vast array of data scientist jobs available. A Data Scientist is a professional who uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from both structured and unstructured data. They are the detectives of the digital age, solving complex business problems by turning raw data into actionable intelligence. The core objective of the role is to empower organizations to make data-driven decisions, optimize operations, and innovate products and services.

Typically, the responsibilities of a Data Scientist encompass the entire data lifecycle. This begins with data acquisition and cleaning, where they gather data from various sources and prepare it for analysis, a critical step often involving building and maintaining robust data pipelines. Following this, they perform exploratory data analysis to identify patterns, trends, and anomalies. A significant part of their work involves developing and implementing machine learning models and statistical models for purposes such as prediction, classification, clustering, and recommendation. They are also responsible for communicating their findings effectively through data visualizations, dashboards, and reports, translating complex technical results into clear, actionable recommendations for stakeholders across the business, including product, engineering, and finance teams.

To succeed in data scientist jobs, a specific skill set is required. Proficiency in programming languages, particularly Python and/or R, is fundamental, along with expert-level skills in SQL for data manipulation and extraction. A strong foundation in statistics and mathematics is crucial for understanding and building models. Practical experience with machine learning libraries (like scikit-learn, TensorFlow, or PyTorch) and data visualization tools (such as Tableau, Power BI, or matplotlib) is highly valued. Beyond technical prowess, soft skills are equally important. Data scientists must possess critical thinking and problem-solving abilities to frame business challenges as analytical problems. Excellent communication and storytelling skills are essential for conveying insights to both technical and non-technical audiences, ensuring that data-driven strategies are understood and implemented.

Common requirements for these positions often include a degree in a quantitative field such as Computer Science, Statistics, Mathematics, or Engineering. While entry-level roles exist, many data scientist jobs seek candidates with proven experience in handling data, building models, and delivering measurable impact. The field is constantly evolving, so a passion for continuous learning about new algorithms, tools, and domains is a key trait of successful professionals. If you are analytical, curious, and driven to find answers hidden within data, exploring data scientist jobs could be your ideal career path.