Hire the Best Data Scientists
in Sweden

I am a Mathematician with good experience in Machine Learning with Python, Tensorflow and Keras. I also know Lean.

Hi, Welcome to my profile. Well! This is Maryam, an avid writer with a natural flair for creativity. To me, writing is a lot more than just a job, it is a way of catharsis for my experiences and observations. I have over 14 years experience of online freelance writing through different platforms, where I have written SEO content and articles on diverse topics, from Business to Fashion, from Technology to Architecture, and from Home Decor to Personal Grooming. I am also managing my own blog where I have a variety of content from different niches. I am a self-motivated person, with excellent communication skills and attention to detail. An added advantage is that I have an extensive experience which enables me to work closely with the deadlines without compromising the quality. Since I enjoy writing and create the content myself, I can assure you about the originality of my pieces of writing. Yes! Hiring me means that you will get the best quality, right on time, without any grammatical errors and plagiarism. Let us get down to details and start working!

Data Scientist & Machine Learning Engineer specializing in production-ready machine learning systems that solve practical problems. I’ve delivered over $2.5M in measurable annual savings by designing, deploying, and unblocking machine learning solutions across Manufacturing, Recruitment, Sales, and Marketing. I adapt data pipelines, models, and evaluation strategies to fit the needs and goals of each business function. Core Expertise: 📌 End-to-end machine learning systems 📌 Data pipelines for robust workflows 📌 Domain-tailored solutions 📌 MLOps aligned with existing workflows 📌 Strategy for ML, data, and platforms Project Highlights: 📈 Built ML capability from zero over 5.5 years at a major steel plant as its first Data Scientist. Scaled the team to 5 people by hiring 2 Data Scientists and 2 Data Engineers, and established an MLOps way-of-working that increased project output by 3.5x. 📈 Removed a key blocker to ML integration by aligning 5 departments around a shared analytics platform, enabling reliable data visualization and model validation — resulting in broad adoption and $1.5M in annual cost savings. 📈 Revived a stalled machine learning model by developing a custom evaluation algorithm, achieving $600K in annual cost savings. 📈 Developed and maintained an end-to-end ML-based image recognition system for a steel plant, resulting in $500K in annual cost savings. 📈 Designed and implemented a data pipeline that aggregated and transferred over 2,300 sensor values to a forecasting model, enabling predictive maintenance for a plate furnace. What I Bring to Every Project: 🔷 Adapting quickly across domains, with a proven ability to learn new fields fast 🔷 Simplifying complex concepts so decision-makers can act with confidence 🔷 Collaborating effectively in cross-functional teams 🔷 Applying both deep and broad expertise in data science and machine learning 🔷 Ensuring clarity and alignment throughout the project 🔷 Delivering well-documented code and smooth handover for long-term maintainability Technical Skills: ❇️ Machine Learning Types (Classification, Regression, Image Recognition, Ranking Models) ❇️ Machine Learning Development (scikit-learn, PyTorch, XGBoost, SHAP) ❇️ Data Engineering (Pandas, SQL, Apache Airflow, Apache Iceberg, Trino, dbt, Databricks) ❇️ Deployment (Docker, FastAPI, Github Actions) ❇️ Data Visualization (Matplotlib, Seaborn, Interactive Dashboards, Grafana) ❇️ Python (Pandas, Numpy, SciPy) I care deeply about delivering practically useful solutions that are capable of delivering value for the long-term. I achieve this by respecting domain knowledge, building reliable systems, and keeping a clear line of sight to business value. I’m focused on projects where my experience can make a meaningful impact and where I can ensure that the delivery meets a high standard. If you’re looking for an experienced Data Scientist who focuses on business value, not just code, I’d love to explore how we can unlock value from your data.

I help organizations transform complex data into actionable insights that drive growth, improve decision making, and create measurable business value. With a PhD in econometrics, statistics, and causal inference and more than a decade of quantitative experience, I specialize in data science, predictive modeling, survey research, marketing analytics, business intelligence, experimentation, and advanced statistical analysis. My experience spans e-commerce, iGaming, insurance, banking, non-profit, automotive, telecom, retail, healthcare, engineering, and research sectors. I have delivered projects ranging from forecasting, predictive modeling, customer analytics, and large-scale survey research to marketing measurement, attribution, and end-to-end analytics platforms. I have extensive experience working with survey and observational data, including questionnaire design support, survey data cleaning and validation, scale and index construction, missing data handling, exploratory analysis, statistical modeling, and results visualization. I have analyzed customer, employee, stakeholder, healthcare, and research survey data using techniques such as logistic regression, count models, multilevel models, Bayesian methods, and causal inference approaches, translating complex findings into actionable recommendations. I have extensive experience building data-driven solutions using Python and SQL, including data analysis, machine learning, forecasting, statistical modeling, Bayesian analysis, survey analytics, customer segmentation, and decision-support systems. My expertise includes Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), incrementality measurement, A/B testing, geo experiments, brand lift studies, causal inference, and Bayesian methods. Experienced in developing Bayesian MMMs using PyMC-Marketing and Google Meridian, I help organizations understand the true drivers of business performance by quantifying channel contribution, adstock and saturation effects, ROI, and budget optimization opportunities. I translate complex analytical findings into practical recommendations that stakeholders can confidently act upon. I have worked extensively with data from Google Ads, Meta, TikTok, LinkedIn, CRM systems, call-tracking platforms, survey platforms, web analytics tools, customer databases, and cloud data warehouses. My technical background includes HubSpot, Datacor, BigQuery, GA4, Snowflake, and custom internal data sources, with a strong focus on data integration, validation, ETL processes, and scalable analytics workflows. Beyond analysis and modeling, I develop dashboards, visualizations, and decision-support applications using Streamlit, Looker, Plotly, and business intelligence platforms. I am passionate about making data accessible and useful, whether through executive dashboards, interactive analytics applications, or clear communication of complex statistical results. I also have extensive experience teaching, mentoring, and collaborating with technical and non-technical stakeholders. As a former university professor, I designed and taught graduate-level courses in statistics, econometrics, quantitative methods, and research design. Whether supporting business leaders, training analysts, or working with cross-functional teams, I focus on delivering solutions that combine analytical rigor with practical business impact. Whether the goal is building predictive models, improving reporting infrastructure, analyzing survey data, conducting statistical research, optimizing marketing investments, measuring incrementality, forecasting business outcomes, or developing advanced analytical solutions, I bring a rigorous quantitative approach and a proven track record of turning data into decisions.

I am passionate programmer who loves coding in python. My specialities include learning new skills and try to implement in real world scenarios, problem solving, GitHub, MongoDB, MySQL,Python, C++,Docker,Linux, Parallel Programming, Machine Learning and Data Analysis. And still there is much more to learn , much more to solve problems and much more to build. Thanks to God who is giving me opportunity to learn and grow.

Greetings! I am a highly skilled and results-driven Data Scientist with a strong background in Computer Engineering. My expertise lies in leveraging advanced analytics and machine learning techniques to derive valuable insights and drive data-driven decision-making. Key Strengths: Data Analysis: Proficient in analyzing large datasets using statistical methods, identifying trends, and extracting meaningful patterns. Machine Learning: Experienced in developing predictive models, classification algorithms, and clustering techniques to solve complex business problems. Programming: Proficient in Python, R, and SQL for data manipulation, analysis, and visualization. Data Visualization: Skilled in creating interactive and insightful visualizations using tools such as Matplotlib, Seaborn, and Tableau. I am confident in my ability to bring a data-driven approach to any project, delivering actionable insights and driving business success. Let's collaborate to transform data into valuable solutions for your organization. Looking forward to contributing to your projects and achieving outstanding results together!