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freelance data science engineer python sql

Mindrift

<div>
 <em>
  Please submit your CV in English and indicate your level of English proficiency.
  <br/>
  <br/>
 </em>
 Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.
 <strong>
  Participation is project-based, not permanent employment.
  <br/>
  <br/>
 </strong>
 <strong>
  What This Opportunity Involves
  <br/>
  <br/>
 </strong>
 While each project involves unique tasks, contributors may:
 <br/>
 <br/>
 <ul>
  <li>
   Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare)
  </li>
  <li>
   Create problems requiring Python programming to solve (using Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn)
  </li>
  <li>
   Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
  </li>
  <li>
   Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction
  </li>
  <li>
   Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility
  </li>
  <li>
   Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency
  </li>
  <li>
   Design end-to-end problems spanning the complete data science pipeline (data ingestion &rarr; cleaning &rarr; EDA &rarr; modeling &rarr; validation &rarr; deployment considerations)
  </li>
  <li>
   Incorporate big data processing scenarios requiring scalable computational approaches
  </li>
  <li>
   Verify solutions using Python with standard data science libraries and statistical methods
  </li>
  <li>
   Document problem statements clearly with realistic business contexts and provide verified correct answers
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Look For
  <br/>
  <br/>
 </strong>
 This opportunity is a good fit for Data Science specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:
 <br/>
 <br/>
 <ul>
  <li>
   5+ years of hands-on data science experience with proven business impact
  </li>
  <li>
   Portfolio of completed projects and publications showcasing real-world problem-solving
  </li>
  <li>
   Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
  </li>
  <li>
   Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications
  </li>
  <li>
   Expert with SQL and database operations for data manipulation and analysis
  </li>
  <li>
   Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
  </li>
  <li>
   Understanding of MLOps practices and model deployment workflows
  </li>
  <li>
   Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
  </li>
  <li>
   Strong written English (C1+)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  How It Works
  <br/>
  <br/>
 </strong>
 Apply &rarr; Pass qualification(s) &rarr; Join a project &rarr; Complete tasks &rarr; Get paid
 <br/>
 <br/>
 <strong>
  Project time expectations
  <br/>
  <br/>
 </strong>
 For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
 <br/>
 <br/>
 <strong>
  Compensation
  <br/>
  <br/>
 </strong>
 On this project, contributors can earn up to
 <strong>
  $90 per hour equivalent
 </strong>
 , depending on their level and pace of contribution.
 <br/>
 <br/>
 Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.
</div>


Freelance Data Science Engineer (Python & SQL)

Openkyber

<div><b>Title: Senior Data Analyst Location: Irving Place, New York, NY(Hybrid) Job Type: Contract Interview:- F2F Interview Job Description:</b>
<p>A Bachelor's Degree in Computer Science or related field with at least 3-5 years' work experience in an enterprise IT environment. Advanced SQL Azure Databricks Data Engineer Associate Certificate full-stack Python Generative AI Knowledge of statistical modeling and machine learning concepts Machine Learning Operations Power BI Dashboards python Pyspark programming Nice To Have JOB SUMMARY Data Analyst w/ ML Experience JOB DESCRIPTION Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems. Mining data from primary and secondary sources, then reorganizing said data in a format that can be easily read by either human or machine. Using statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.</p>
<p>Required Skills/Experience (Skills that the successful candidate(s) must have) Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics , or related field. Strong experience in machine learning algorithms , predictive modeling, and data mining. Proficiency in Python (required) for data science workloads. Strong SQL (required) knowledge and experience with relational databases. Proficiency in PySpark(required) for data science workloads. Minimum 3 years of experience with data visualization tools such as Power BI, Dax Queries, and best practices. Experience with Azure Databricks , Oracle , and modern data science libraries (e.g., scikit-learn, pandas, NumPy). Experience with GenAI and large language models. Ability to interpret complex datasets and produce actionable insights. Must know how to analyze the root cause of dashboard errors. Have experience in ML Ops and have strong coding background. Have experience with Natural Language Processing (NLP). Knowledge or experience with A/B Testing. Working knowledge of designing, training, and implementing machine learning models. Familiarity with cloud-based infrastructure Excellent communication and problem-solving skills. 7 or more years of experience in data science and machine learning engineering.</p>
<p>Additional Skills (Skills that are a plus, but not required) Knowledge of statistical methods and experimental design.</p>
<p>Responsibilities Advanced Analytics &amp; Machine Learning Design, develop, and optimize machine learning models (forecasting, classification, clustering). Apply data mining techniques to uncover patterns and insights in large datasets. Perform feature engineering, model validation, and performance tuning. Explore and deploy modern AI and ML approaches to enhance automation and analytics.</p>
<p>Data Preparation &amp; Quality Prepare structured and unstructured data for modeling and advanced analysis. Develop scripts and tools for data cleansing, validation, and enrichment. Collaborate with Data Engineering to maintain efficient data pipelines. Identify data quality issues and propose remediation.</p>
<p>Analytics, Insights &amp; Reporting Conduct deep-dive analyses to identify trends and improvement opportunities. Communicate complex findings in clear, concise ways to technical and non-technical stakeholders. Support the development of dashboards, metrics, and analytical solutions.</p>
<p>Cross-Team Collaboration Work with architects, engineers, and analysts to define analytical requirements. Contribute to conceptual data model design and workflow optimization. Promote best practices in machine learning, analytics, and data governance.</p>
<p><b>For applications and inquiries, contact:</b> hirings@openkyber.com</p></div>

Cognos Business Intelligence Analyst

RSC Solutions

<div>
 <br/>
 <br/>
 <strong>
  TITLE: Senior Data Platform Engineer w/DBT &amp; Airflow
  <br/>
 </strong>
 <strong>
  LOCATION: New York City (midtown)
  <br/>
  HYBRID ONSITE 4 DAYS IN THE OFFICE
  <br/>
  NO C2C 3RD PARTY VENDORS!!
  <br/>
  NO RELOCATION!!
  <br/>
  <br/>
 </strong>
 <strong>
  JOB DESCRIPTION:
  <br/>
  EXPERIENCED DATA ENGINEER MUST HAVE HANDS ON EXPERIENCE WITH DEPLOYMENTS, DBT, AIRFLOW, PYTHON AND AWS.
  <br/>
  <br/>
 </strong>
 The Data Platform Engineer will be responsible for the design, build, and maintenance of Company's data platforms used for both analytics and for the integration of business and customer-facing applications. This role plays a critical part in advancing cloud-native data architecture and enabling reliable, scalable analytics and production data use cases. The Data Platform Engineer will design, build, and operate core components of the enterprise data platform, including robust data pipelines, scalable cloud infrastructure, and optimized data models that power business intelligence and operational systems across the organization. This position requires strong hands-on engineering expertise along with the ability to contribute to platform-level architecture, ensuring the data ecosystem is performant, secure, and positioned to scale with evolving business needs.
 <br/>
 <br/>
 <br/>
 <strong>
  Specific Functions/Activities&nbsp;
 </strong>
 <strong>
  SUMMARY:
 </strong>
 <ul>
  <li>
   Design, build, and maintain scalable, reliable AWS-based data architecture
  </li>
  <li>
   <strong>
    Develop and optimize production-grade Python data pipelines
   </strong>
  </li>
  <li>
   <strong>
    Own end-to-end ELT workflows using DBT and Apache Airflow
   </strong>
  </li>
  <li>
   Design, implement, and optimize data models to support analytics and operational reporting
  </li>
  <li>
   Improve platform reliability, observability, and performance across the data stack
  </li>
  <li>
   Contribute to architectural decisions for scalability, security, and cost optimization
  </li>
  <li>
   Partner with DevOps to implement CI/CD, infrastructure-as-code, and automated deployments
  </li>
  <li>
   Evaluate and recommend new technologies to evolve MSG's data platform
  </li>
 </ul>
 <strong>
  REQUIRED EXPERIENCE:
 </strong>
 <ul>
  <li>
   <strong>
    4-7 years experience building and maintaining production data pipelines
   </strong>
  </li>
  <li>
   <strong>
    4 years Python development experience (production-grade code)
   </strong>
  </li>
  <li>
   <strong>
    2 years experience with DBT
   </strong>
  </li>
  <li>
   <strong>
    2 years experience with Apache Airflow (or equivalent orchestration tools)
   </strong>
  </li>
  <li>
   Strong SQL and data modeling expertise (dimensional normalized modeling)
  </li>
  <li>
   Hands-on experience with AWS data services (S3, Redshift, Glue, Athena, DynamoDB)
  </li>
  <li>
   Experience designing scalable data architectures in cloud environments
  </li>
  <li>
   Experience troubleshooting and supporting production systems
  </li>
  <li>
   Strong communication skills and ability to work directly with business stakeholders
  </li>
  <li>
   Bachelor's degree in Computer Science, Engineering, or related field
  </li>
 </ul>
 <strong>
  Preferred
 </strong>
 <ul>
  <li>
   Infrastructure as Code (Terraform or CloudFormation)
  </li>
  <li>
   CI/CD and DevOps practices
   <br/>
  </li>
 </ul>
</div>


Senior Data Engineer with DBT and Airflow-Onsite NYC

<div>
 <p>
  <strong>
   Role: Senior Data Analytics Engineer with AI Initiatives (Must)
  </strong>
 </p>
 <p>
  <strong>
   Location: New York/ Remote
  </strong>
 </p>
 <p>
  <strong>
   Experience: 5 - 10 years
  </strong>
 </p>
 <p>
  <strong>
   Duration: Full time
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Description:
  </strong>
 </p>
 <p>
  We are looking for a Lead Engineer to build and maintain scalable data pipelines and data platforms that support analytics, business Intelligence, reporting, and AI initiatives. In this role, you will work closely with data architects, analysts, and business stakeholders to develop reliable data solutions and ensure high-quality data is available across the organization.
 </p>
 <p>
  This is a
  <strong>
   hands-on engineering role
  </strong>
  focused on designing efficient data pipelines, improving data infrastructure, and enabling teams to leverage data effectively.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design, build, and maintain scalable
   <strong>
    data pipelines and ETL/ELT workflows
   </strong>
   to ingest and transform data from multiple sources
  </li>
  <li>
   Develop and optimize
   <strong>
    batch and near real-time data processing pipelines
   </strong>
   for analytics and reporting
  </li>
  <li>
   Build and maintain
   <strong>
    data warehouse and data lake structures
   </strong>
   to support business intelligence and analytics use cases
  </li>
  <li>
   Implement and maintain
   <strong>
    data models
   </strong>
   that support efficient querying and reporting
  </li>
  <li>
   Improve performance and scalability of data systems through
   <strong>
    query optimization, indexing, and partitioning strategies
   </strong>
  </li>
  <li>
   Implement
   <strong>
    data quality checks, monitoring, and logging
   </strong>
   to ensure reliability of data pipelines
  </li>
  <li>
   Exposure to
   <strong>
    AI initiatives
   </strong>
   and experience
   <strong>
    building data pipelines
   </strong>
   supporting
   <strong>
    AI workflows
   </strong>
  </li>
  <li>
   Work with data architects and engineering teams to implement
   <strong>
    scalable data platform designs
   </strong>
  </li>
  <li>
   Collaborate with analysts, BI developers, and business stakeholders to deliver data solutions that support business needs
  </li>
  <li>
   Maintain documentation for data pipelines, data models, and data workflows
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    5 - 10 years of experience
   </strong>
   in Data Engineering and GenAI and Data Scientist and AI Engineer
  </li>
  <li>
   Strong experience with
   <strong>
    SQL and Python
   </strong>
   for data processing and transformation
  </li>
  <li>
   Experience building and maintaining
   <strong>
    ETL/ELT pipelines
   </strong>
  </li>
  <li>
   Solid understanding of
   <strong>
    data warehousing concepts and dimensional data modeling
   </strong>
  </li>
  <li>
   Experience working with
   <strong>
    cloud data platforms or modern data infrastructure
   </strong>
  </li>
  <li>
   Familiarity with
   <strong>
    workflow orchestration tools
   </strong>
   such as
   <strong>
    Airflow
   </strong>
   or similar
  </li>
  <li>
   Understanding of
   <strong>
    API-based data ingestion and data integration patterns
   </strong>
  </li>
  <li>
   Strong problem-solving and collaboration skills
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Education
  </strong>
 </p>
 <p>
  Bachelor's or master's degree in computer science
  <strong>
   , Engineering, Information Systems, or a related field
  </strong>
  , or equivalent practical experience.
 </p>
</div>


AI Data Engineer

Workwhile

<div><div><p>Location</p><div>
New York; San Francisco; Seattle; Toronto</div></div><div><p>
Employment Type</p><div>
Full time</div></div><div><p>
Location Type</p><div>
Hybrid</div></div><div><p>
Department</p><div><div>
Operations</div><p>
Marketplace Ops</p></div></div><div><p>
Compensation</p><ul><div><div>
Estimated Base Salary</div><p>
$160K &ndash; $180K &bull; Offers Equity</p></div></ul><div><div>
This range represents the good-faith estimate of the base salary/wage we reasonably expect to pay at the time of hire. Final offer amounts are determined by multiple factors, including seniority, experience, skills, and geography.</div></div></div></div>
<br><div><div><div><b>About WorkWhile</b></div><p>
WorkWhile is on a mission to help workers earn a better living and live better lives. More than 80 million Americans work hourly jobs, often with unpredictable schedules that pay close to minimum wage and offer limited benefits, leading to financial instability.</p><p>
WorkWhile is revolutionizing frontline work by creating a more flexible and efficient labor market. Powered by AI, the WorkWhile platform helps businesses quickly access high-quality talent. Workers benefit from same-day pay, free telehealth services, upskilling, and the ability to choose shifts that match their skills and schedules.</p><p>
We have the audacious goal to align incentives and solve inefficiencies in the labor market, disrupting the $650 billion staffing and recruiting market. Backed by Khosla Ventures and recognized by the Inc. 5000 for 10x growth, WorkWhile is reshaping the future of work.</p><p><b>
About the role</b></p><p>
WorkWhile is on a mission to help workers earn a better living and live better lives&mdash;and we're looking for a data-driven <b>Growth Marketing Engineer</b> to help us reach every worker who needs us. You won't just support growth; you <i>are</i> the growth engine. You'll be the technical engine behind how we acquire, engage, and retain workers at scale&mdash;sitting at the intersection of Engineering, Data Science, and Marketing to turn insight into impact.</p><p>
This isn't a traditional &quot;set it and forget it&quot; role. You are a <b>self-starter</b> who thrives on rapid experimentation and seeing the direct impact of what you build on company growth metrics. You&rsquo;ll be responsible for scaling our reach across performance channels and ensure our marketing stack is a seamless, automated machine.</p><p><b>
What you'll do</b></p><ul><li><div><b>
Architect Growth Loops:</b> Design, build, code, and deploy automated marketing workflows across SMS, email, ads, and in-app channels to drive worker sign-ups and retention.</div></li><li><div><b>
Optimize Performance Ads:</b> Build technical integrations and custom scripts for Search, Display, and Retargeting platforms (Google, Meta, etc.) to improve attribution and bidding efficiency.</div></li><li><div><b>
Data Infrastructure:</b> Write complex <b>SQL</b> to extract insights from our data warehouse and use <b>Python</b> to build tools, scrapers, or automation scripts that streamline marketing operations.</div></li><li><div><b>
Experimentation at Scale:</b> Partner with product teams on A/B testing frameworks across the worker journey&mdash;from landing page optimization to referral program mechanics.</div></li><li><div><b>
Technical Stack Management:</b> Act as the technical owner of our marketing automation platform</div></li></ul><p><b>
Who you are</b></p><ul><li><div><b>
Analytically Rigorous:</b> You live in the data and obsess over moving metrics. You know what good CAC, LTV and conversion rates look like</div></li><li><div><b>
Technical Generalist:</b> You are highly proficient in <b>Python</b> and <b>SQL</b>, with the ability to navigate APIs and build robust integrations as well as treat growth as a core product function</div></li><li><div><b>
Automation expert:</b> You&rsquo;ve built and scaled marketing systems and know where they break</div></li><li><div><b>
Marketing Savvy:</b> You have a deep understanding of the performance marketing ecosystem, including search/display ads and lifecycle marketing (Email/SMS)</div></li><li><div><b>
Self-Directed:</b> You are comfortable with ambiguity. You can identify a bottleneck in the growth funnel and build the solution without a detailed spec sheet</div></li></ul><p><b>
Requirements</b></p><ul><li><div><b>
3+ years of experience</b> in growth engineering, data engineering, or a highly technical marketing ops role</div></li><li><div>
Expertise in <b>SQL</b> (PostgreSQL/BigQuery/Snowflake) and <b>Python</b> for data analysis, automation and building growth tools</div></li><li><div>
Experience with <b>TypeScript and React/React Native</b> - ability to understand and work with our frontend stack to implement growth tools and experiments</div></li><li><div>
Hands-on experience with <b>Marketing Automation</b> (e.g., Braze, Iterable, Klaviyo, or Hubspot) and analytics tools (e.g. Amplitude)</div></li><li><div>
Experience managing and optimizing <b>Performance Ad</b> technical setups (Pixels, CAPI, GTM)</div></li></ul><p>
Proven track record of building automated systems for <b>SMS, Email, and In-App</b> messaging</p><p><b>
Benefits &amp; Perks</b></p><ul><li><div>
Remote-friendly work culture with office hubs in SF, NY, Seattle &amp; Toronto</div></li><li><div>
In-person company offsites</div></li><li><div>
Medical, dental, &amp; vision coverage</div></li><li><div>
Flexible time off</div></li><li><div>
401(k) with employer match</div></li><li><div>
WFH stipend to support your home office needs</div></li></ul><p>
WorkWhile has a diverse, mission-driven, and supportive culture&mdash;we look for people who want to take ownership, are energized by ambiguity, and strive to make a lasting impact. If this resonates with you, we&rsquo;d love to chat!</p><p>
WorkWhile is an Equal Opportunity Employer. Women, minorities, individuals with disabilities and protected veterans are encouraged to apply.</p></div></div><p></p>

Growth Marketing Engineer, Worker Experience

Data Scientist (Python & SQL) - Freelance AI Trainer

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.<br>
</li>
<li><div><div><div>10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree.</div></div></div></li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.<br>
</li>
<li>12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
The Workspace Collaboration Data Science team empowers product teams for Drive, Docs, Sheets, Slides, Vids (and more) through development of key metrics, data-driven insights, modeling, experimentation and other forms of causal inference to grow product adoption and AI usage.</p>
The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.<div></div><div><br>
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div></div><p></p><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Define, own and evolve product success metrics. Report, analyze and forecast trends of key product metrics and make recommendations to improve them.</li>
<li>Lead the design, analysis, and interpretation of product experiments. Proactively perform data exploration to understand user behavior and identify opportunities for improving and growing Workspace products.</li>
<li>Apply technical expertise with observational data analysis, modeling, and causal inference to answer the most important product questions.</li>
<li>Partner with Product, Engineering, UX and cross-functional teams to influence, prioritize and support product strategy.</li>
<li>Deliver effective presentations of data-driven insights and recommendations to multiple levels of stakeholders.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Staff Product Data Scientist, Workspace Collaboration Data Science

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