5534 Data Science Jobs - Page 32

Job Overview We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. ResponsibilitiesCredit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.Qualifications2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.A deep understanding of using cloud computing infrastructure and data pipelines in production.Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

Responsibilities: * Design, develop & deploy generative AI models using ML algorithms on GCP cloud. * Optimize model performance through data analysis & experimentation.

Responsibilities - Owning Data Pipeline from Web to Athena to Email, end-to-end Youll make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week day. Personalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you? 2+ years of professional data engineering experience Someone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch points You have strong experience in data analysis, growth marketing, or audience development (media or newsletters? Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them up Youre comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goals Problem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguity Excited to join a lean team in a big company that moves quickly

Job Overview We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. Responsibilities - Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team. Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications - 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred. Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions. A deep understanding of using cloud computing infrastructure and data pipelines in production. Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done. Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

Job Overview We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. Responsibilities Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers. Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team. Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors. Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications - 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred. Excellent software engineering and programming skills, especially Python and SQL. A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions. A deep understanding of using cloud computing infrastructure and data pipelines in production. Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done. Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher. The drive to make a positive impact on customers' lives.

1. Job Purpose The Senior Data Analytics Analyst will play a key role in delivering hands-on analytics solutions across the UK and Ireland. This role focuses on bespoke report building, dashboard development, and advanced data analysis using technologies such as Power BI, Microsoft Fabric, Snowflake, Azure, AWS, Python, SQL, and R. Experience in data science is highly advantageous, including the application of machine learning and predictive modelling to solve business problems 2. Accountabilities & Activities • Design and build interactive dashboards and reports using Power BI and Microsoft Fabric. • Perform advanced data analysis and visualisation to support business decision-making. • Develop and maintain data pipelines and queries using SQL and Python. • Apply data science techniques such as predictive modelling, classification, clustering, and regression to solve business problems and uncover actionable insights. • Perform feature engineering and data preprocessing to prepare datasets for machine learning workflows. • Build, validate, and tune machine learning models using tools such as scikit-learn, TensorFlow, or similar frameworks. • Deploy models into production environments and monitor their performance over time, ensuring they deliver consistent value. • Collaborate with stakeholders to translate business questions into data science problems and communicate findings in a clear, actionable manner. • Use statistical techniques and hypothesis testing to validate assumptions and support decision-making. • Document data science workflows and maintain reproducibility of experiments and models. • Support the Data Analytics Manager in delivering analytics projects and mentoring junior analysts. • Design and build interactive dashboards and reports using Power BI and Microsoft Fabric. 3. Qualifications, Knowledge & Experience • Professional Certifications (preferred or in progress): - Microsoft Certified: Power BI Data Analyst Associate (PL-300) - SnowPro Core Certification (Snowflake) - Microsoft Certified: Azure Data Engineer Associate - AWS Certified: Data Analytics Specialty • Strong technical expertise in Power BI, Microsoft Fabric, Snowflake, SQL, Python, and R. • Experience with Azure Data Factory, Databricks, Synapse Analytics, and AWS Glue. • Hands-on experience in building and deploying machine learning models. • Ability to translate complex data into actionable insights. • Excellent problem-solving and communication skills. 4. Judgement Skills Balances team development with delivery priorities and business needs. Makes informed decisions on technical design, resource allocation, and delivery timelines. Evaluates project outcomes and identifies opportunities for team and process improvement. Encourages experimentation while maintaining delivery discipline and governance. 5. Freedom Of Action Acts as a key liaison between technical teams and business stakeholders. 6. Dimensions Financial: Supports budgeting and cost optimisation for analytics projects. Contributes to revenue growth through data-driven client solutions. Non-Financial: Drives adoption of modern analytics tools and practices. Builds strong relationships across business units and with external clients. 7. Environment Build strong relationships and influence key decision makers. Able to work under pressure and adapt to chang

Full Time Role at EssentiallySports for Data Growth EngineerEssentiallySports is the home for the underserved fan, delivering storytelling that goes beyond the headlines. As a media platform, we combine deep audience insights with cultural trends, to meet fandom where it lives and where it goes next. ValuesFocus on the user and all else will followHire for Intent and not for ExperienceBootstrapping gives you the freedom to serve the customer and the team instead of investorInternet and Technology untap the nichesAction oriented, integrity, freedom, strong communicators, and responsibilityAll things equal, one with high agency wins The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. ResponsibilitiesOwning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you?2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters? Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

Full Time Role at EssentiallySports for Data Growth Engineer EssentiallySports is the home for the underserved fan, delivering storytelling that goes beyond the headlines. As a media platform, we combine deep audience insights with cultural trends, to meet fandom where it lives and where it goes next. ValuesFocus on the user and all else will followHire for Intent and not for ExperienceBootstrapping gives you the freedom to serve the customer and the team instead of investorInternet and Technology untap the nichesAction oriented, integrity, freedom, strong communicators, and responsibilityAll things equal, one with high agency wins The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. ResponsibilitiesOwning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you? 2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters? Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

Full Time Role at EssentiallySports for Data Growth EngineerEssentiallySports is the home for the underserved fan, delivering storytelling that goes beyond the headlines. As a media platform, we combine deep audience insights with cultural trends, to meet fandom where it lives and where it goes next. ValuesFocus on the user and all else will followHire for Intent and not for ExperienceBootstrapping gives you the freedom to serve the customer and the team instead of investorInternet and Technology untap the nichesAction oriented, integrity, freedom, strong communicators, and responsibility The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. ResponsibilitiesOwning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you?2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters? Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

Full Time Role at EssentiallySports for Data Growth EngineerEssentiallySports is the home for the underserved fan, delivering storytelling that goes beyond the headlines. As a media platform, we combine deep audience insights with cultural trends, to meet fandom where it lives and where it goes next. ValuesFocus on the user and all else will followHire for Intent and not for ExperienceBootstrapping gives you the freedom to serve the customer and the team instead of investorInternet and Technology untap the nichesAction oriented, integrity, freedom, strong communicators, and responsibility The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. ResponsibilitiesOwning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you?2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters? Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. ResponsibilitiesOwning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you? 2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. Responsibilities Owning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you? 2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. Responsibilities Owning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you? 2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters? Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

Full Time Role at EssentiallySports for Data Growth EngineerEssentiallySports is the home for the underserved fan, delivering storytelling that goes beyond the headlines. As a media platform, we combine deep audience insights with cultural trends, to meet fandom where it lives and where it goes next. ValuesFocus on the user and all else will followHire for Intent and not for ExperienceBootstrapping gives you the freedom to serve the customer and the team instead of investorInternet and Technology untap the nichesAction oriented, integrity, freedom, strong communicators, and responsibilityAll things equal, one with high agency winsEssentiallySports is a top 10 sports media platform in the U. S. , generating over a billion pageviews a year and 30m+ monthly active users per month. This massive traffic fuels our data-driven culture, allowing us to build owned audiences at scale through organic growtha model we take pride in, with zero CAC. The next phase of ES growth is around newsletter initiative, in less than 9 months, weve built a robust newsletter brand with 700,000+ highly engaged readers and impressive performance metrics:5 newsletter brands700k+ subscribersOpen rates of 40%-46%. The role is for a data engineer with growth and business acumen, in the permissionless growth team. Someone who can connect the pipelines of millions of users, but at the same time knit a story of the how and why. ResponsibilitiesOwning Data Pipeline from Web to Athena to Email, end-to-endYoull make the key decisions and see them through to successful user sign upUse Data Science to find real insights, which translates to user engagementPushing changes every week dayPersonalization at Scale: Leverage fan behavior data to tailor content and improve lifetime value. Who are you?2+ years of professional data engineering experienceSomeone who spends time thinking about business insights as much as they do on engineeringIs a self-starter, and drives initiativesIs excited to pick up AI, and integrate it at various touch pointsYou have strong experience in data analysis, growth marketing, or audience development (media or newsletters? Even better). Have an awareness about Athena, Glue, Jupyter, or intent to pick them upYoure comfortable working with tools like Google Analytics, SQL, email marketing platforms (Beehiiv is a plus), and data visualization tools. Collaborative and want to see the team succeed in its goalsProblem solving, proactive and solution oriented mindset, to spot opportunities and translate into real growthAbility to thrive in startups with a fast-paced environment and take ownership for working through ambiguityExcited to join a lean team in a big company that moves quickly

Job Overview Branch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.ResponsibilitiesCredit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.Qualifications2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.A deep understanding of using cloud computing infrastructure and data pipelines in production.Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

Job OverviewBranch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. Responsibilities Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.A deep understanding of using cloud computing infrastructure and data pipelines in production.Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.ResponsibilitiesCredit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions. A deep understanding of using cloud computing infrastructure and data pipelines in production.Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

Job Overview We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting. Responsibilities Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.A deep understanding of using cloud computing infrastructure and data pipelines in production. Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

Position: Junior Software Engineer (AI & Data Structures) Location: Nagpur Job Type: Full Time About the Role: We are seeking a driven and talented fresher with internship experience to join our engineering team. As a Junior Software Engineer, youll contribute to building efficient, scalable software solutions with a strong emphasis on Artificial Intelligence and data structures in C programming. Key Responsibilities: Develop and maintain reliable, high-performance code in C, focusing on data structures and algorithms. Support the design and implementation of AI models and algorithms under the mentorship of senior engineers. Collaborate with cross-functional teams to gather requirements and contribute to innovative technical solutions. Stay updated with the latest trends and best practices in AI and software development. Qualifications: Bachelors degree in Artificial Intelligence, Data Science, Computer Science, Engineering, or a related field. Prior internship experience demonstrating hands-on application of AI concepts and C programming. Strong grasp of data structures, algorithms, and their implementation in C. Familiarity with AI/ML concepts, tools, and frameworks. Strong analytical and problem-solving skills with a willingness to learn and adapt quickly. Excellent communication and teamwork abilities.

Experience : 3 to 5 years Job Type: Hybrid Location: Hyderabad About the Role: We are seeking a highly skilled and motivated Machine Learning Specialist with a strong background in data science and a deep understanding of clinical supply chain/Supply Chain operations . This role will be instrumental in developing predictive models, optimizing logistics, and driving data-driven decision-making across our clinical trial supply chain. Key Responsibilities: Design, develop, and deploy machine learning models to forecast clinical supply needs, optimize inventory, and reduce waste. Collaborate with clinical operations, supply chain, and IT teams to identify data sources and integrate ML solutions into existing workflows. Analyze large datasets from clinical trials, logistics systems, and external sources to uncover trends and actionable insights. Develop tools and dashboards to support real-time decision-making and scenario planning. Ensure model performance, scalability, and compliance with regulatory standards (e.g., GxP, 21 CFR Part 11). Stay current with advancements in ML/AI and apply best practices to clinical supply chain challenges. Qualifications: Masters or PhD in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in machine learning, data science, or AI, preferably in a healthcare or life sciences setting. Hands-on experience with clinical supply chain processes, including demand forecasting, IRT systems, and logistics planning. Proficiency in Python, R, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Strong understanding of statistical modeling, time series forecasting, and optimization techniques. Excellent communication skills and ability to work cross-functionally in a fast-paced environment. Preferred: Experience with clinical trial data (e.g., EDC, CTMS, IRT). Familiarity with regulatory requirements in clinical research. Knowledge of cloud platforms (AWS, Azure, GCP) and MLOps practices.

We are urgently hiring for Senior Data Scientist with Biz2x at Noida As a Biz2x Data Scientist, you will shape the company's data-centric culture, work closely with our engineering team to develop our analytics infrastructure, and collaborate closely with our Chief Risk Officer on developing, validating, and automating our customer conversion and underwriting models While a background in financial services is not required, you must be passionate about tackling complex data challenges for the benefit of small and medium businesses everywhere Job Responsibility: - Drive the ongoing advancement and refinement of Biz2Credit's credit decisioning & pricing model optimizing risk and return while dramatically reducing decision cycle times Continuously evaluate alternative data sources and structures to document and improve the efficacy of our customer conversion models and processes Harness the power of Biz2Credit's technology to proactively identify emerging risks as well as opportunities with our customers Play a key role in the design and implementation of ongoing operational and risk reporting and analytics Work on data projects and proposals involving Biz2Credit's financial services partners worldwide (banks, non-banks, debt investors, equity investors and others) to analyze, classify and visualize credit-related data Perform ad hoc analyses on customer, business, and portfolio trends to generate actionable insights for internal and external stakeholders Manage multiple projects and priorities while delivering accurate & timely results in a fastpaced environment Requirements Degree in Statistics, Applied Mathematics, Engineering, Computer Science or other quantitative fields from leading university; Advanced degree preferred 3-6 years of experience in applied data science or machine learning roles Hands-on experience with LLMs and GenAI applications Expertise in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn Strong experience in deep learning, NLP, and generative models (e-g , VAEs, GANs, Diffusion models) Experience with prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), or model distillation Proficiency in SQL, data wrangling, and working with large datasets Familiarity with MLOps tools (e-g , MLflow, Airflow, Kubeflow) and cloud platforms (AWS/GCP/Azure) Preferred Qualifications Published work in ML/AI journals or major conferences (NeurIPS, ICML, ACL, CVPR, etc) Experience building and deploying LLM-powered applications in production Background in reinforcement learning, time series forecasting, or causal inference Understanding data privacy, model fairness, and ethical AI consideration

Position 1: Databricks Expert for Data Science Experience: 6+ Years Contract Duration: 6 Months Location: Remote,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad,Mumbai, Hyderabad Availability: Immediate preferred Key Responsibilities: Design and implement advanced data science workflows using Azure Databricks. Collaborate with cross-functional teams to scale data pipelines. Optimize and fine-tune PySpark jobs for performance and efficiency. Support real-time analytics and big data use cases in a remote-first agile environment. Required Skills: Proven experience in Databricks, PySpark, and big data architecture. Ability to work with data scientists to operationalize models. Strong understanding of data governance, security, and performance.

Career Category Information Systems Job Description Let s do this. Let s change the world. In this vital role you will collaborate with business partners, service owners and IS peers to develop predictive models and insights across the US Commercial Organization. This position will innovate and build significant business impact through the use of sophisticated analytics techniques to help Amgen with its mission to serve patients by helping them get the therapies they need. Flexible Commuter role to Amgen India office. You will work on-site 2-3 days a week. This position will be primarily responsible for: Working collaboratively with cross-functional teams on projects and/or programs with aims to systematically derive insights that ultimately derive substantial business value for Amgen and our patients Identifying business needs and proposing potential analytics approaches for solutions Crafting and deploying a framework to supervise the performance of various campaigns, and tactics at a granular level Leading measurement and tracking of various omnichannel CX enablement initiatives Supporting the development of data science, machine learning prototypes, proof of concepts and models for testing various omnichannel strategies Communicating analysis ideas, progress and results to leadership and business partners What we expect of you We are all different, yet we all use our unique contributions to serve patients. The [vital attribute] professional we seek is a [type of person] with these qualifications. Basic Qualifications: Doctorate degree ORdata science and/or analytics experience Master s degree and 4 to 6 years of data science and/or analytics experience OR Bachelor s degree and 6 to 8 years of data science and/or analytics experience OR Diploma and 10 to 12 years of data science and/or analytics experience Preferred Qualifications: Relevant work experience in campaign measurement, marketing analytics and resource optimization in the pharma domain Programming experience with Python, R, or SAS and experience with ML libraries like scikit-learn, MLib, or TensorFlow Experience working with large datasets, experience working with distributed computing tools (Spark, Hive, etc.) is a plus Ability to communicate analysis in a clear, detailed, and practical manner Passion for learning and staying on top of current developments in sophisticated analytics Biotech / Pharma experience What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now and make a lasting impact with the Amgen team. careers.amgen.com .

You are a strategic thinker passionate about driving solutions in Data Science . You have found the right team. As a Data Science professional within our Asset Management team , you will spend each day defining, refining and delivering set goals for our firm The Asset Management Data Science team is focused on enhancing and facilitating various steps in the investment process ranging from financial analysis and portfolio management to client services and advisory. You will utilize a large collection of textual data including financial documents, analyst reports, news, meeting notes and client communications along with more typical structured datasets. You will apply the latest methodologies to generate actionable insights to be directly consumed by our business partners. Are you excited about using data science and machine learning to make a real impact in the asset management industryDo you enjoy working with cutting-edge technologies and collaborating with a team of dedicated professionalsIf so, the Data Science team at JP Morgan Asset Management could be the perfect fit for you. Here s why Real-World Impact Your work will directly contribute to improving investment process and enhancing client experiences and operational process, making a tangible difference in our asset management business. Collaborative Environment Join a team that values collaboration and teamwork. You ll work closely with business stakeholders and technologists to develop and implement effective solutions. Continuous Learning We support your professional growth by providing opportunities to learn and experiment with the latest data science and machine learning techniques. Job Responsibilities Collaborate with internal stakeholders to identify business needs and develop NLP/ML solutions that address client needs and drive transformation. Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to enhance informed decision-making and improve workflow efficiency, which can be utilized across investment functions, client services, and operational process. Collect and curate datasets for model training and evaluation. Perform experiments using different model architectures and hyperparameters, determine appropriate objective functions and evaluation metrics, and run statistical analysis of results. Monitor and improve model performance through feedback and active learning. Collaborate with technology teams to deploy and scale the developed models in production. Deliver written, visual, and oral presentation of modeling results to business and technical stakeholders. Stay up-to-date with the latest research in LLM, ML and data science. Identify and leverage emerging techniques to drive ongoing enhancement. Required qualifications, capabilities, and skills Advanced degree (MS or PhD) in a quantitative or technical discipline or significant practical experience in industry. Minimum of 4 years of experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, summarization, personalization, classification or forecasting. Advanced python programming skills with experience writing production quality code Good understanding of the foundational principles and practical implementations of ML algorithms such as clustering, decision trees, gradient descent etc. Hands-on experience with deep learning toolkits such as PyTorch, Transformers, HuggingFace. Strong knowledge of language models, prompt engineering, model finetuning, and domain adaptation. Familiarity with latest development in deep learning frameworks. Ability to communicate complex concepts and results to both technical and business audiences. Preferred qualifications, capabilities, and skills Prior experience in an Asset Management line of business Exposure to distributed model training, and deployment Familiarity with techniques for model explainability and self validation You are a strategic thinker passionate about driving solutions in Data Science . You have found the right team. As a Data Science professional within our Asset Management team , you will spend each day defining, refining and delivering set goals for our firm The Asset Management Data Science team is focused on enhancing and facilitating various steps in the investment process ranging from financial analysis and portfolio management to client services and advisory. You will utilize a large collection of textual data including financial documents, analyst reports, news, meeting notes and client communications along with more typical structured datasets. You will apply the latest methodologies to generate actionable insights to be directly consumed by our business partners. Are you excited about using data science and machine learning to make a real impact in the asset management industryDo you enjoy working with cutting-edge technologies and collaborating with a team of dedicated professionalsIf so, the Data Science team at JP Morgan Asset Management could be the perfect fit for you. Here s why Real-World Impact Your work will directly contribute to improving investment process and enhancing client experiences and operational process, making a tangible difference in our asset management business. Collaborative Environment Join a team that values collaboration and teamwork. You ll work closely with business stakeholders and technologists to develop and implement effective solutions. Continuous Learning We support your professional growth by providing opportunities to learn and experiment with the latest data science and machine learning techniques. Job Responsibilities Collaborate with internal stakeholders to identify business needs and develop NLP/ML solutions that address client needs and drive transformation. Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to enhance informed decision-making and improve workflow efficiency, which can be utilized across investment functions, client services, and operational process. Collect and curate datasets for model training and evaluation. Perform experiments using different model architectures and hyperparameters, determine appropriate objective functions and evaluation metrics, and run statistical analysis of results. Monitor and improve model performance through feedback and active learning. Collaborate with technology teams to deploy and scale the developed models in production. Deliver written, visual, and oral presentation of modeling results to business and technical stakeholders. Stay up-to-date with the latest research in LLM, ML and data science. Identify and leverage emerging techniques to drive ongoing enhancement. Required qualifications, capabilities, and skills Advanced degree (MS or PhD) in a quantitative or technical discipline or significant practical experience in industry. Minimum of 4 years of experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, summarization, personalization, classification or forecasting. Advanced python programming skills with experience writing production quality code Good understanding of the foundational principles and practical implementations of ML algorithms such as clustering, decision trees, gradient descent etc. Hands-on experience with deep learning toolkits such as PyTorch, Transformers, HuggingFace. Strong knowledge of language models, prompt engineering, model finetuning, and domain adaptation. Familiarity with latest development in deep learning frameworks. Ability to communicate complex concepts and results to both technical and business audiences. Preferred qualifications, capabilities, and skills Prior experience in an Asset Management line of business Exposure to distributed model training, and deployment Familiarity with techniques for model explainability and self validation

Lead AI/ML tech projects using Agile/Scrum. Design, deploy & optimize ML models (NLP, predictive analytics). Drive AI automation & data-driven decisions. Cross-functional leadership.