data science specialist

Information Technology Senior Management Forum

<div><div>Posted Date
9/15/2025
</div><div>Description
<div>Senior Data Scientist, AI Foundations
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. 
As a Data Scientist at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One&rsquo;s award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One&rsquo;s digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies.
In this role, you will:<ul><li>
Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.</li><li>
Leverage a broad stack of technologies &mdash; Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more &mdash; to reveal the insights hidden within huge volumes of numeric and textual data.</li><li>
Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.</li><li>
Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.</li><li>
Flex your interpersonal skills to translate the complexity of your work into tangible business goals.</li></ul>
The Ideal Candidate is:<ul><li>
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it&rsquo;s about making the right decision for our customers.</li><li>
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.</li><li>
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You&rsquo;re not afraid to share a new idea.</li><li>
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.</li><li>
Technical. You&rsquo;re comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.</li><li>
Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences.</li><li>
You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF.</li><li>
You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products.</li></ul>
Basic Qualifications:<ul><li>
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:<ul><li>
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics</li><li>
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration</li></ul></li></ul>
Preferred Qualifications:<ul><li>
Master&rsquo;s Degree in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics), or PhD in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics)</li><li>
Experience working with AWS</li><li>
At least 2 years&rsquo; experience in Python, Scala, or R</li><li>
At least 2 years&rsquo; experience with machine learning</li><li>
At least 2 years&rsquo; experience with SQL
</li></ul>Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
New York, NY: $145,100 - $165,600 for Sr Assoc, Data Science 

San Jose, CA: $145,100 - $165,600 for Sr Assoc, Data Science 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Data Scientist, AI Foundations
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. 
As a Data Scientist at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One&rsquo;s award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One&rsquo;s digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies.
In this role, you will:<ul><li>
Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.</li><li>
Leverage a broad stack of technologies &mdash; Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more &mdash; to reveal the insights hidden within huge volumes of numeric and textual data.</li><li>
Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.</li><li>
Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.</li><li>
Flex your interpersonal skills to translate the complexity of your work into tangible business goals.</li></ul>
The Ideal Candidate is:<ul><li>
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it&rsquo;s about making the right decision for our customers.</li><li>
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.</li><li>
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You&rsquo;re not afraid to share a new idea.</li><li>
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.</li><li>
Technical. You&rsquo;re comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.</li><li>
Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences.</li><li>
You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF.</li><li>
You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products.</li></ul>
Basic Qualifications:<ul><li>
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:<ul><li>
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics</li><li>
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration</li></ul></li></ul>
Preferred Qualifications:<ul><li>
Master&rsquo;s Degree in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics), or PhD in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics)</li><li>
Experience working with AWS</li><li>
At least 2 years&rsquo; experience in Python, Scala, or R</li><li>
At least 2 years&rsquo; experience with machine learning</li><li>
At least 2 years&rsquo; experience with SQL
</li></ul>Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
New York, NY: $145,100 - $165,600 for Sr Assoc, Data Science 

San Jose, CA: $145,100 - $165,600 for Sr Assoc, Data Science 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>
</div><div>Salary
145,100.00 - 165,600.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Senior Data Scientist, AI Foundations

QUARTERMASTER

<div>Job Description: We are seeking a Data Scientist to help us turn vast, high-dimensional sensor data into actionable insights for our customers&mdash;and smarter models for our edge-deployed systems. This role sits at the intersection of data analytics, machine learning, and product development. You&rsquo;ll analyze aggregate data collected across fleets and deployments to extract meaningful patterns, trends, and outliers that support operational intelligence and system-wide performance improvements. Just as critically, you&rsquo;ll work closely with our machine perception and modeling teams to create feedback loops that inform model retraining, edge-case detection, and system calibration. This role is ideal for someone who thrives in full-cycle data science work&mdash;from framing a question to deploying a data product.<h2 class="jobSectionHeader">
Key Responsibilities:</h2><ul><li>
Analyze large volumes of structured and unstructured data from field deployments to uncover trends, anomalies, and actionable insights for customers</li><li> 
Develop scalable analytics pipelines to support customer-facing dashboards, reports, and intelligence products</li><li> 
Collaborate with product and customer success teams to frame high-value business and operational questions and translate them into data science workflows</li><li> 
Identify performance gaps, failure modes, and drift in edge-deployed models by analyzing historical outputs, sensor metadata, and ground-truth comparisons</li><li> 
Partner with the modeling team to design feedback mechanisms for continuous learning, dataset enrichment, and model retraining</li><li> 
Build tools and internal services for data visualization, metric tracking, and experimentation across field data</li><li> 
Contribute to the design and refinement of metrics for evaluating perception, detection, and fusion performance across time and space</li><li> 
Ensure data quality and integrity across the pipeline, including logging validation, schema enforcement, and anomaly detection</li><li> 
Stay current with best practices in large-scale data analytics, monitoring, and applied ML, and advocate for their integration into team workflows</li></ul><h2 class="jobSectionHeader"> 
Qualifications (Preferred):</h2><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Statistics, Computer Science, or a related field</li><li> 
3&ndash;5 years of experience in applied data science, with a track record of translating raw data into production insights or tools</li><li> 
Proficiency in Python and common data science libraries (e.g., pandas, numpy, scikit-learn, matplotlib/seaborn, SQL)</li><li> 
Experience working with time-series, geospatial, or multi-sensor data in production environments</li><li> 
Strong analytical thinking and statistical modeling skills, including clustering, regression, and anomaly detection</li><li> 
Familiarity with ML operations concepts like dataset versioning, data labeling workflows, and model monitoring</li><li> 
Excellent communication skills for presenting complex insights to both technical and non-technical stakeholders</li><li> 
Bonus: experience supporting or analyzing ML systems at the edge, or in environments like maritime, automotive, or aerospace domains</li></ul> 
Work Environment:<ul><li>
This is a remote position with collaboration via online tools.</li><li>
Flexible working hours with occasional deadlines requiring high availability.</li><li>
Opportunity to work on innovative projects with a global impact.</li></ul> 
Benefits:<ul><li>
Competitive salary</li><li>
Flexible work hours and the option for remote work.</li><li>
Opportunities for professional development and continued education.</li></ul></div>

Data Scientist

CAI (Computer Aid, Inc.)

Req number: R6198
 
Employment type: Full time
 
Worksite flexibility: Onsite Who we are
 CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.
 
Job Summary We are looking for a motivated Data Scientist ready to take us to the next level! If you understand Python, SQL, and cloud computing to build data pipelines, develop predictive models and are looking forward to your next career move, apply now
 
Job Description
 We are looking for a Data Scientist . This position will be full-time and Onsite Gurugram.
 
What You’ll Do
 Analyze large and complex logistics datasets to uncover patterns and optimize operations.
 Build and deploy machine learning models for forecasting, route optimization, anomaly detection, and other analyses.
 Write efficient Python and SQL code to develop ETL workflows and data pipelines.
 Collaborate with cross-functional teams—including Data Engineers, Operations, and Business stakeholders—to define requirements and deliver data-driven solutions.
 Work with cloud platforms such as AWS, Azure, or GCP to architect scalable, cloud-native data science solutions.
 Stay informed about new developments in Data Science, ML, and GenAI, and apply them to business problems.
 Present findings and model results clearly to both technical and non-technical audiences.
 
What You'll Need
 Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related disciplines.
 2-4 years in Python (libraries like pandas, NumPy, scikit-learn).
 Strong SQL skills for querying and manipulating large relational datasets.
 Hands-on experience with cloud platforms (AWS/Azure/GCP).
 Solid understanding of statistical analysis and machine learning fundamentals.
 Analytical mindset with attention to detail and problem-solving capabilities.
 Excellent verbal and written communication skills.
 
Preferred
 Exposure to Generative AI frameworks or large language models (e.g., Open AI GPT, Hugging Face Transformers).
 Familiarity with cloud-native ML tools (e.g., Sage Maker, Azure ML, Vertex AI).
 Experience with CI/CD pipelines and version control (e.g., Git).
 
Physical Demands
 Sedentary work that involves sitting or remaining stationery most of the time with occasional need to move around the office to attend meetings, etc.
 Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor.
 
Reasonable accommodation statement
 If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.

Principal Global Services

<div>Responsibilities:
<ul><li>Responsible for answering business questions using machine learning techniques, algorithms and statistical models.</li><li>
Gathering and integrating large volumes of data, performs analysis, interprets results, and develops actionable insights and recommendations.</li><li>
Responsible for evaluating statistical/machine learning models to determine validity of analyses, testing models, and developing visualizations to help clients make business decisions.</li><li>
Collaborate &amp; Partner closely with business and data teams and deliver data science solutions to identified business problem</li><li>
Researching and applying knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions</li><li>
Coaching, mentoring, reviewing work of junior data scientist</li></ul>
Qualifications: 
<div></div><ul><li>
BE/B.Tech with 7+ years of experience in Data Science</li><li>
Deep knowledge of Statistics, Mathematics, Optimization, Machine Learning theory and quantitative
 
techniques.</li><li>
Extensive programming experience in Python, SQL. Proficient with machine learning libraries such as SciKit-Learn,SciPy, Keras, Tensorflow, PyTorch etc.</li><li>
Experience working with large datasets including structured/unstructured data</li><li>
Knowledge in evaluating and making decisions around the use of new or existing machine learning, data analysis, optimization techniques/tools for a project.</li><li>
Experience in model evaluation, tuning and performance.</li><li>
Experience with Cloud technologies (AWS, Azure, etc.)</li><li>
Passion for picking up new techniques/technologies</li><li>
Self motivated attitude and desire to work on applied problems</li></ul></div><div></div>

Lead Data Scientist

PtteM

<div>
 
 We are a fast-growing digital commerce company, delivering innovative technology solutions to millions of users globally. Our data science team plays a key role in shaping product decisions, optimizing business operations, and delivering personalized user experiences. We are looking for an experienced
 
 Data Scientist
 
 who is equally comfortable with
 
 Predictive Modeling
 
 and
 
 Natural Language Processing (NLP) / Large Language Models (LLMs)
 
 to deliver full-stack data solutions from raw data to production-ready models.As a Data Scientist, you will work across the entire analytics lifecycle &mdash; from
 
 data exploration and feature engineering
 
 to
 
 model development, deployment, and monitoring
 
 . You will develop predictive models for recommendation systems, demand forecasting and customer behavior analysis, while also building NLP/LLM-powered applications for search, personalization, and automation.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and deploy
 
 ML models
 
 for recommendation, forecasting and optimization problems.
 </li>
 <li>
 Build
 
 NLP and LLM-based solutions
 
 for text classification, summarization, semantic search, and conversational AI.
 </li>
 <li>
 Perform end-to-end data science tasks: data collection, cleaning, feature engineering, and exploratory analysis.
 </li>
 <li>
 Implement
 
 full-stack machine learning pipelines
 
 from experimentation to production deployment.
 </li>
 <li>
 Leverage cloud-based environments (especially GCP) for scalable model training and serving.
 </li>
 <li>
 Collaborate with Product, Engineering, and Business teams to translate requirements into actionable data solutions.
 </li>
 <li>
 Continuously monitor, evaluate, refine and report model performance.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
 </li>
 <li>
 4+ years of experience in applied data science, with expertise in both
 
 predictive analytics and NLP
 
 .
 </li>
 <li>
 Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and experience with ML frameworks (TensorFlow, PyTorch).
 </li>
 <li>
 Hands-on experience with
 
 Hugging Face Transformers
 
 and LLM services.
 </li>
 <li>
 Strong SQL skills and experience with data warehouses (BigQuery or other DBs).
 </li>
 <li>
 Familiarity with MLOps practices and data orchestration tools (MLflow, Airflow).
 </li>
 <li>
 Excellent problem-solving and communication skills.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Experience with
 
 vector databases
 
 (Pinecone, FAISS, Weaviate) for semantic search and retrieval-augmented generation (RAG).
 </li>
 <li>
 Domain experience in e-commerce or large-scale digital platforms.
 </li>
 <li>
 Understanding of microservices architecture and API-first model serving (e.g.,
 
 Flask
 
 ,
 
 FastAPI
 
 ).
 </li>
 <li>
 Exposure to real-time analytics and streaming data processing (Kafka, Flink).
 </li>
 </ul>
 
 
 
 
 
 Why Join Us?
 
 
 <ul>
 <li>
 Work on
 
 end-to-end data science projects
 
 that combine predictive analytics, NLP, and LLMs.
 </li>
 <li>
 Opportunity to impact millions of users with data-driven innovation.
 </li>
 <li>
 Collaborative and agile work environment.
 </li>
 <li>
 Flexible working arrangements and professional development opportunities.
 </li>
 <li>
 Competitive compensation and benefits package.
 </li>
 </ul>
 
 
</div>

HR POD Careers

<div>
 
 Requirements:
 
 
 
 <ul>
 <li>
 Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field.
 </li>
 <li>
 4+ years of hands-on experience in Machine Learning, Data Science, or Quantitative Research.
 </li>
 <li>
 Strong proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
 </li>
 <li>
 Solid understanding of statistical modeling, regression, and time-series analysis.
 </li>
 <li>
 Experience designing and deploying predictive and deep learning models.
 </li>
 <li>
 Strong analytical and problem-solving skills, with the ability to work independently.
 </li>
 <li>
 Excellent verbal and written communication skills in English.
 </li>
 <li>
 Experience in quantitative finance, trading, or investment-related projects.
 </li>
 <li>
 Familiarity with systematic strategies, risk modeling, or portfolio optimization.
 </li>
 <li>
 Exposure to cloud platforms (AWS, GCP, Azure) and large-scale data infrastructure.
 </li>
 <li>
 Knowledge of financial data APIs, Bloomberg/Refinitiv, or alternative datasets.
 
 
 
 </li>
 </ul>
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Design and implement predictive and regression models on large datasets, leveraging both tree-based methods and deep learning techniques.
 </li>
 <li>
 Build and maintain robust data integration pipelines in Python.
 </li>
 <li>
 Apply advanced ML/AI approaches to generate, clean, and validate proprietary datasets.
 </li>
 <li>
 Conduct backtesting, validation, and performance evaluation of data-driven models.
 </li>
 <li>
 Collaborate with cross-functional teams to translate research insights into practical solutions.
 </li>
 <li>
 Continuously monitor and refine models to improve accuracy, scalability, and efficiency.
 
 </li>
 </ul>
</div>

Data Scientist (Onsite, Lahore, PKR Salary)

Infogain

<div>ROLES &amp; RESPONSIBILITIES
<div>Core Skills
 Expert knowledge of statistics and probability theory Proficiency in at least one programming language such as Python, R, or SQL Advanced experience with data visualization tools such as Tableau or PowerBI Expert understanding of machine learning algorithms and models Advanced knowledge of data cleaning and preprocessing techniques Experience with data analysis and interpretation Strong communication and presentation skills</div>
EXPERIENCE
<ul><div>8-11 Years</div>
</ul>SKILLS
<ul><div>Primary Skill: Data Science</div>
<div>Sub Skill(s): Data Science
</div><div>Additional Skill(s): Python, Data Modeling, Data Science</div>
</ul>ABOUT THE COMPANY
Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley. We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail &amp; CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence. We accelerate experience-led transformation in the delivery of digital platforms. Infogain is also a Microsoft (NASDAQ: MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP).

Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Krak&oacute;w, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.</div>

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